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Published online by Cambridge University Press: 19 January 2017
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- The Measure of All MindsEvaluating Natural and Artificial Intelligence, pp. 483 - 540Publisher: Cambridge University PressPrint publication year: 2017
References
and (2004). Apprenticeship learning via inverse reinforcement learning. In International Conference on Machine Learning, pages 1–8. ACM International Conference Proceeding Series 69. ACM
, , , and (2011). Relative quantity judgments in South American sea lions (Otaria flavescens). Animal Cognition, 14(5):695–706.Google Scholar
(1904). A law of acceleration. Chapter 34 in(1905) “The education of Henry Adams”. Houghton Mifflin.
, , , , , , , , , , , and (2012). Mapping the landscape of human-level artificial general intelligence. AI Magazine, 33(1):25–42.Google Scholar
, , and (2016). I-athlon: Towards a multidimensional Turing test. AI Magazine, 37(1):78–84.Google Scholar
AERA, APA & NCME (1999). Standards for educational and psychological testing. American Educational Research Association.
(2015). Juzgado Nacional de Primera Instancia en lo Contencioso Administrativo Federal, Argentinian Court 34, 21-oct-2015, MJ-JU-M-95342-AR.
and (2013). Numberwithout language: Comparative psychology and the evolution of numerical cognition. Frontiers in Psychology, 4.Google Scholar
(2013). Cooperative games and multiagent systems. The Knowledge Engineering Review, 28(4):381–424.Google Scholar
and (1999). Component-based knowledge spaces in problem solving and inductive reasoning. In and (Eds.) Knowledge spaces: Theories, empirical research, and applications, pages 15–40. Psychology Press.
and (2012). The experience of being born: A natural context for learning to suckle. International Journal of Pediatrics, 2012:ID 129328, 11 pages.Google Scholar
, , , , , , and (2010). Keel data-mining software tool: Data set repository, integration of algorithms and experimental analysis framework. Journal of Multiple-Valued Logic and Soft Computing, 17:255–287.Google Scholar
(1988). Do zero correlations really exist among measures of different intellectual abilities. Educational and Psychological Measurement, 48(2):275–280.Google Scholar
, , , K., , , , , , and (2013). Syntax-guided synthesis. In and (Eds.) Formal Methods in Computer-Aided Design (FMCAD), 2013, pages 1–17. IEEE.
, , , and (2002). Beyond the Turing test: Performance metrics for evaluating a computer simulation of the human mind. In International Conference on Development and Learning, 2002, pages 147–152. IEEE.
and (2011). Child language acquisition: Contrasting theoretical approaches. Cambridge University Press.
, , , , , , , , , , , , and (2015). Competitions for benchmarking: Task and functionality scoring complete performance assessment. IEEE Robotics & Automation Magazine, 22(3):53–61. Benchmarks available at http://rockinrobotchallenge.eu.Google Scholar
(1993). Evidence from the rat for a general factor that underlies cognitive performance and that relates to brain size: Intelligence. Neuroscience Letters, 153(1):98–102.Google Scholar
(2000). The g factor in non-human animals. In , , and , editors, The nature of intelligence, volume 233, pages 79–95. John Wiley.
and (2003). Teamwork in animals, robots, and humans. Advances in the Study of Behavior, 33:1–48.Google Scholar
, , and (2011). Robotics competitions as benchmarks for AI research. The Knowledge Engineering Review, 26(1):11–17.Google Scholar
and (2003). The Newell Test for a theory of cognition. Behavioral and Brain Sciences, 26(5):587–601.Google Scholar
(2004). A flexible approach to quantifying various dimensions of environmental complexity. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2004 PerMIS Workshop, August 24–26, 2004, pages 192–197. NIST.
, , , , , , and (2015). VQA: Visual question answering. CoRR arXiv preprint:1505.00468.
, , Van , and (2006). Computational depth: Concept and applications. Theoretical Computer Science, 354(3):391–404.Google Scholar
, , and (2010). Deep machine learning – a new frontier in artificial intelligence research. Computational Intelligence Magazine, 5(4):13–18.Google Scholar
and (2015). How we're predicting AI–or failing to. In , and (Eds.) Beyond artificial intelligence, pages 11–29. Springer.
and (2002). Tactile memory of deaf-blind adults on four tasks. Scandinavian Journal of Psychology, 43(1):73–79.Google Scholar
and (2009). Computational complexity: A modern approach. Cambridge University Press.
, , and (2010). ConsScale: A pragmatic scale for measuring the level of consciousness in artificial agents. Journal of Consciousness Studies, 17(3–4):131–164.Google Scholar
, , , , , , , and (2009). Cognitive developmental robotics: A survey. IEEE Transactions on Autonomous Mental Development, 1(1):12–34.Google Scholar
(1956). An introduction to cybernetics. Chapman and Hall.
, , , and (1992). Working memory, automaticity, and problem difficulty. Advances in Psychology, 91:301–329.Google Scholar
and (2010). Evolution for automatic assessment of the difficulty of Sokoban boards. In IEEE Congress on Evolutionary Computation (CEC), pages 1–8. IEEE.
(1950). I, robot. Gnome Press.
ASPCR(1999). American Society for the Prevention of Cruelty to Robots. http://www.aspcr.com/.
, , and (2008). Effective complexity and its relation to logical depth. CoRR ArXiv preprint:0810.5663.
, , , , , and (2015). Possible and necessary winners of partial tournaments. Journal of Artificial Intelligence Research, 54:493–534.Google Scholar
and (2013). UCI machine learning repository. University of California, Irvine, School of Information and Computer Sciences. http://archive.ics.uci.edu/ml.
, , , , and (2012a). Crowd IQ: Aggregating opinions to boost performance. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, volume 1, pages 535–542.Google Scholar
, , , , and (2012b). Personality and patterns of facebook usage. In Proceedings of the 3rd Annual ACM Web Science Conference, pages 24–32. ACM.
(1718). The essays, or councils, civil and moral. H. Clark.
, , , and (2002). Representing and parameterizing agent behaviors. In Proceedings of Computer Animation, 2002, pages 133–143. IEEE.
(2000). Hierarchic social entropy: An information theoretic measure of robot group diversity. Autonomous Robots, 8(3):209–238.Google Scholar
, , , , , , , , , , , , , , , , , , , , , , , , , and (2000). Compendium of the minutes of plenary discussion. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMISWorkshop, pages 543–556. NIST Special Publication 970, Gaithersburg, MD.
and , editors(2013). Intrinsically motivated learning in natural and artificial systems. Springer.
and (2008). History of modern personality theory and research. In Handbook of personality: Theory and research, pages 3–26. Guilford Press.
and (2014). Not as smart as we think: A study of collective intelligence in virtual groups. Proceedings of Collective Intelligence.
and (2012). Universality probability of a prefix-free machine. Philosophical Transactions of the Royal Society, Series, 370:3488–3511.Google Scholar
and (2013). The development of arithmetic concepts and skills: Constructive adaptive expertise. Routledge.
, , , and (2011). Comparative experimental studies on spatial memory and learning in rats and robots. Journal of Intelligent and Robotic Systems, 63:361–397.Google Scholar
and (1991). A reconsideration of testing for competence rather than for intelligence. American Psychologist, 46(10):1012.Google Scholar
(2004). The future of ability testing: What happened to the science of mental ability. Measurement, 2(1):33–54.Google Scholar
and (2012). An analysis framework for ad hoc teamwork tasks. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, Volume 1, pages 357–364. International Foundation for Autonomous Agents and Multiagent Systems.
(2004). Measuring intelligence: Facts and fallacies. Cambridge University Press.
, et al.(1994). The role of emotion in believable agents. Communications of the ACM, 37(7):122–125.Google Scholar
(2004). What is thought?
MIT Press.
(1969). Scales of infant development. Psychological Corporation.
(1993). Bayley scales of infant development: Manual. Psychological Corporation.
BBC(2003). Is txt mightier than the word? BBC News, 4 March. http://news.bbc.co.uk/go/pr/fr/-/2/hi/uk_news/2814235.stm.
BBC (2014a). Court in Argentina grants basic rights to orangutan. BBC News, 21 December. http://www.bbc.com/news/world-latin-america-30571577.
BBC (2014b). US chimpanzee Tommy ‘has no human rights’ – court. BBC News, 4 December. http://www.bbc.com/news/world-us-canada-30338231.
(1982). Chimpocentrism: Bias in cognitive ethology. Journal of Human Evolution, 11(1):3–17.Google Scholar
(2004). Autopoiesis and cognition in the game of life. Artificial Life, 10(3):309–326.Google Scholar
(2003). The dynamics of active categorical perception in an evolved model agent. Adaptive Behavior, 11(4):209–243.Google Scholar
and (2015). Information processing and dynamics in minimally cognitive agents. Cognitive Science, 39(1):1–38.Google Scholar
, , and (1991). Cognitive and psychometric analysis of analogical problem solving. Springer.
, , , and (2013). The arcade learning environment: An evaluation platform for general agents. Journal of Artificial Intelligence Research, 47:253–279.Google Scholar
(2008). Social behavior of bacteria: From physics to complex organization. European Physical Journal B, 65(3):315–322.Google Scholar
(2009). Learning from bacteria about natural information processing. Annals of the New York Academy of Sciences, 1178(1):78–90.Google Scholar
(2012). Interpreting the MMPI-2-RF. University of Minnesota Press.
(2015). Establishing a human baseline for the Winograd schema challenge. In M. Glass and J. H. Kim (Eds.). Modern AI and Cognitive Science Conference, CEUR Workshop Proceedings, 1353:39–45.Google Scholar
, , , , and (1998). Information distance. IEEE Transactions on Information Theory, 44(4):1407–1423.Google Scholar
, , , , and (2016). Brain size predicts problem-solving ability in mammalian carnivores. Proceedings of the National Academy of Sciences, 113(9):2352–2357.Google Scholar
(1780). An introduction to the principles of morals and legislation. T. Payne.
, , and (2004). An empirical exploration of the difficulty function. In , , (Eds.) Computer Safety, Reliability, and Security, LNCS 3219, pages 60–71. Springer.
, , , , , , , and (2014). Modeling biological processes for reading comprehension. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, EMNLP, pages 1499–1510. Association for Computational Linguistics.
(2007). Report on panel discussion on can the development of intelligent robots be benchmarked? Concepts and issues from epigenetic robotics. In and , editors, Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems, pages 167–181. NIST.
, , , , ,, , , , et al.(2012). A hippocampal cognitive prosthesis: Multi-input, multi-output nonlinear modeling and VLSI implementation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(2):198–211.Google Scholar
, , and (2007). Knitting for fun: A recursive sweater. In Fun with algorithms, pages 53–65. Springer.
, , and (2015). Can machine intelligence be measured in the same way as human intelligence. Künstliche Intelligenz, 29(3):291–297.Google Scholar
(2014). A note on chances and limitations of Psychometric AI. In KI 2014: Advances in Artificial Intelligence, pages 49–54. Springer.
, , , , , , , , and (2010). Genetic covariation between brain volumes and IQ, reading performance, and processing speed. Behavior genetics, 40(2):135–145.Google Scholar
, , et al.(2013). Agent-based models of strategies for the emergence and evolution of grammatical agreement. PloS ONE, 8(3):e58960.Google Scholar
(1980). Intellektik statt KI – Ein ernstgemeinter Vorschlag. Rundbrief der Fachgruppe Künstliche Intelligenz in der Gesellschaft für Informatik, 22:15–16.Google Scholar
, , , and (2002). Machine intelligence quotient: Its measurements and applications. Fuzzy Sets and Systems, 127(1):3–16.Google Scholar
, , and (1998). How to measure the machine intelligence quotient (MIQ): Two methods and applications. In World Automation Congress (WAC). TSI Press.
(1909). Les idées modernes sur les enfants. Flammarion.
and (1905). New methods for the diagnosis of the intellectual level of subnormals. L'année Psychologique, 12:191–244.Google Scholar
(1993). Moral considerability and universal consideration. Environmental Ethics, 15(4):313–332.Google Scholar
and (2009). Rooks use stones to raise the water level to reach a floating worm. Current Biology, 19(16):1410–1414.Google Scholar
, , , , and (2010). Is the urothelium intelligent. Neurourology and Urodynamics, 29(4):598–602.Google Scholar
and (2002). The origins of human nature: Evolutionary developmental psychology. American Psychological Association.
and (2000). Two reasons to abandon the false belief task as a test of theory of mind. Cognition, 77(1):B25–B31.Google Scholar
and (1975). Toward a mathematical theory of inductive inference. Information and Control, 28(2):125–155.Google Scholar
(1790). Beytrage zur Naturgeschichte, 2 vols. Göttingen: Dieterich.
(2002). From the Binet–Simon to the Wechsler–Bellevue: Tracing the history of intelligence testing. Journal of Clinical and Experimental Neuropsychology, 24(3):383–405.Google Scholar
and (2013). Birdsong, speech, and language: Exploring the evolution of mind and brain. MIT Press.
, , and (1999). Swarm intelligence: From natural to artificial systems. Oxford University Press.
(1939). The total library. In The total library: Non-fiction 1922–1986, translated by , pages 214–216
Penguin Press, London, 2000. Pages 214–216. Translated by Eliot Weinberge.
(1957). The book of imaginary beings. Originally published in Portuguese as Manual de zoología fantástica
, Fce-Breviarios; English version 2002, Random House.
(1964). Other inquisitions (1937–1952), Translated by . University of Texas Press.
(2005). Measuring the mind: Conceptual issues in contemporary psychometrics. Cambridge University Press.
, , , and (2006). Collective representational content for shared extended mind. Cognitive Systems Research, 7(2):151–174.Google Scholar
(2014). Superintelligence: Paths, dangers, strategies. Oxford University Press.
and (2009). Cognitive enhancement: Methods, ethics, regulatory challenges. Science and Engineering Ethics, 15(3):311–341.Google Scholar
and (2001). Language acquisition and conceptual development, volume 3. Cambridge University Press.
and (2008). Psychoeducational assessment of students who are visually impaired or blind: Infancy through high school. Region 4 Education Service Center.
and (2011). The consciousness quotient: A new predictor of the students' academic performance. Procedia – Social and Behavioral Sciences, 11:245–250.Google Scholar
(2000). In light of artificial intelligence, the science of mental ability is either silly or pointless. Psycoloquy, 11, Article 43.Google Scholar
(2011). Psychometric artificial intelligence. Journal of Experimental & Theoretical Artificial Intelligence, 23(3):271–277.Google Scholar
, , and (2003). Creativity, the Turing test, and the (better) Lovelace test. In , editor, The Turing test: The elusive standard of artificial intelligence, pages 215–239. Springer.
and (2003). What is artificial intelligence? Psychometric AI as an answer. In International Joint Conference on Artificial Intelligence, pages 887–893. Morgan Kaufmann.
(1926). The philosophy of Francis Bacon. Cambridge University Press.
(2015). What do you think about machines that think?, Annual question. Edge.org. http://edge.org/annual-question/what-do-you-think-about-machinesthat- think.
(2001). Stigmergy – an intelligence metric for emergent distributed behaviors. In Workshop on Performance Metrics for Intelligent Systems, pages 186–192. NIST.
, , and (1993). Nelson-Denny reading test: Manual for scoring and interpretation, forms G & H. Riverside.
(2016). Modeling progress in AI. In AAAI 2016 Workshop on AI, Ethics, and Society.
(2010). Robots should be slaves. In , editor, Close engagements with artificial companions: Key social, psychological, ethical and design issues, pages 63–74. John Benjamins.
(1987). The validity of learning potential assessment. In , editor, Dynamic testing, pages 173–195. Guilford Press.
, , and (2011). Amazon's mechanical turk a new source of inexpensive, yet high-quality, data. Perspectives on Psychological Science, 6(1):3–5.Google Scholar
, , and (1991). Ratman and its relation to other multi-agent testbeds. Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Research Report, RR-91-09.
and (2008). Human-robot interaction metrics and future directions. In Workshop on Metrics for Human-Robot Interaction, page 1. School of Computer Science, University of Hertforshire.
(2007). Deconstructing developmental psychology. Routledge.
(1998). Test accommodations for students with disabilities.
ERIC.
, , , and (2014). The end is nigh: Generic solving of text-based CAPTCHAs. In Proceedings of the 8th USENIX Conference on Offensive Technologies, pages 3–3. USENIX Association.
(1949). The structure of the mind: A review of the results of factor analysis. British Journal of Educational Psychology, 19(2–3):100–111, 176–199.Google Scholar
and (2010). Improving intelligence: A literature review. Swiss Medical Weekly, 140(19–20):266–272.Google Scholar
, , and De (2008). A comprehensive survey of multiagent reinforcement learning. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(2):156–172.Google Scholar
(1999). Evolutionary psychology: The new science of the mind. Allyn and Bacon.
(1872). Erewhon. William Brendon.
and (1998). The effect of humans on the cognitive development of apes. In , , and , editors, Reaching into thought: The minds of the great apes, pages 371–403. Cambridge University Press.
and (2012). Fundamentals of gifted education: Considering multiple perspectives. Routledge.
(2003). Nonclassical connectionism should enter the decathlon. Behavioral and Brain Sciences, 26(05):603–604.Google Scholar
and (2011). Plants: Adaptive behavior, root-brains, and minimal cognition. Adaptive Behavior, 19(3):155–171.Google Scholar
(1995). Feral children and clever animals: Reflections on human nature. Oxford University Press.
and (2015). Developmental robotics: From babies to robots. MIT Press.
and (2006). Shared system for ordering small and large numbers in monkeys and humans. Psychological Science, 17(5):401–406.Google Scholar
(1980). Towards a process model of human personality traits. Artificial Intelligence, 15(1):49–74.Google Scholar
, , and (2014). The nineteenth mental measurements yearbook. Buros Center for Testing. http://buros.org/mental-measurementsyearbook.
, , and (1990). What one intelligence test measures: A theoretical account of the processing in the Raven Progressive Matrices test. Psychological Review, 97:404–431.Google Scholar
(2008). Is Google making us stupid. Yearbook of the National Society for the Study of Education, 107(2):89–94.Google Scholar
(2011). The shallows: What the Internet is doing to our brains. W. W. Norton.
(1981). Ability and task difficulty in cognitive psychology. Educational Researcher, pages 11–21.Google Scholar
(1993). Human cognitive abilities: A survey of factor-analytic studies. Cambridge University Press.
and (2005). Task similarity measures for transfer in reinforcement learning task libraries. In International Joint Conference on Neural Networks, volume 2, pages 803–808. IEEE.
(2007). Minds and computers: An introduction to the philosophy of artificial intelligence. Edinburgh University Press.
, , , and (1998). Personality traits and social attitudes in multiagent cooperation. Applied Artificial Intelligence, 12(7–8):649–675.Google Scholar
(1946). Description and measurement of personality. World Book Company.
, , and (1970). Handbook for the sixteen personality factor questionnaire (16 PF). In clinical, educational, industrial, and research psychology, for use with all forms of the test. Institute for Personality and Ability Testing.
, , , , , and (2014). The workshop on computational personality recognition 2014. In Proceedings of the ACM International Conference on Multimedia, pages 1245–1246. ACM.
, , , and (2013). The workshop on computational personality recognition 2013. AAAI Technical Report WS-13-01.
(1975). A theory of program size formally identical to information theory. Journal of the ACM, 22(3):329–340.Google Scholar
(1977). Algorithmic information theory. IBM Journal of Research and Development, 21(4):350–359.Google Scholar
(1982). Gödel's theorem and information. International Journal of Theoretical Physics, 21(12):941–954.Google Scholar
(2002). On the intelligibility of the universe and the notions of simplicity, complexity and irreducibility. In Grenzen und Grenzüberschreitungen, XIX. Deutscher Kongress fur Philosophie, Bonn, 23.-27. September 2002.ArXiv preprint: math/0210035.
(2010). The singularity: A philosophical analysis. Journal of Consciousness Studies, 17(9-10):7–65.Google Scholar
(1990). What kind of information processing is intelligence? In The foundation of artificial intelligence – a sourcebook, pages 14–46. Cambridge University Press.
(2008). Constructing grammar: A computational model of the emergence of early constructions. PhD thesis, University of California at Berkeley.
and (2011). L'homme, l'animal et la machine. CNRS éditions.
, , et al.(1998). The universal declaration of animal rights: Comments and intentions. Ligue Française des Droits de l'Animal.
and (2007). Natural and artificial meta-configured altricial information-processing systems. International Journal of Unconventional Computing, 3(3):211–239.Google Scholar
(1999). The search for simplicity: A fundamental cognitive principle. Quarterly Journal of Experimental Psychology: Section A, 52(2):273–302.Google Scholar
, , , and (2015). Empiricism and language learnability. Oxford University Press.
and (2003). Simplicity: A unifying principle in cognitive science. Trends in Cognitive Sciences, 7(1):19–22.Google Scholar
and (2007). ‘Ideal learning’ of natural language: Positive results about learning from positive evidence. Journal of Mathematical Psychology, 51(3):135–163.Google Scholar
(2010). Sophistication and logical depth revisited. In 2010 IEEE/ACS International Conference on Computer Systems and Applications (AICCSA), pages 1–4. IEEE.
(2011). Radical embodied cognitive science. MIT Press.
, , , and (2015a). Observation, communication and intelligence in agent-based systems. In , , and , editors, Artificial General Intelligence – 8th International Conference, AGI 2015, Berlin, Germany, July 22–25, 2015, Proceedings, pages 50–59. Springer.
, , , , and (2015b). Measuring universal intelligence in agent-based systems using the anytime intelligence test. Technical Report 2015/279, Faculty of Information Technology, Clayton, Monash University.
(1965). Aspects of the theory of syntax. MIT Press.
(1998). Minimalist inquiries: The framework. MIT Working Papers in Linguistics.
and (2008). Language as shaped by the brain. Behavioral and Brain Sciences, 31(5):489–509.Google Scholar
, , , and (2012). Detecting automation of Twitter accounts: Are you a human, bot, or cyborg. IEEE Transactions on Dependable and Secure Computing, 9(6):811–824.Google Scholar
and (2008). Intelligence: A brief history. John Wiley.
and (2005). Clustering by compression. IEEE Transactions on Information Theory, 51(4):1523–1545.Google Scholar
(2004). Natural-born cyborgs: Minds, technologies, and the future of human intelligence. Oxford University Press.
(2015). Elementary school science and math tests as a driver for AI: Take the Aristo challenge!
Proceedings of the Twenty-Seventh Conference on Innovative Applications of Artificial Intelligence, pages 4019–4021.Google Scholar
and (2016). My computer is an honor student – but how intelligent is it? Standardized tests as a measure of AI. AI Magazine, 37(1):5–12.Google Scholar
and (1995). Co-evolution of pursuit and evasion II: Simulation methods and results. In , , , , and , editors, From Animals to Animats 4: Proceedings of the Fourth International Conference on Simulation of Adaptive Behavior, pages 506–515. MIT Press.
(1965). The intrinsic computational difficulty of functions. In (Ed.), Proceedings of the 1964 Congress for Logic, Methodology, and the Philosophy of Science, pages 24–30. Studies in Logic and the Foundations of Mathematics. North-Holland.
(1977). Sampling techniques. John Wiley.
, , and (2006). The cylindrical structure of the Wechsler Intelligence Scale for Children IV: A retest of the Guttman model of intelligence. Intelligence, 34(6):587–591.Google Scholar
and (1988). How evaluation guides AI research: The message still counts more than the medium. AI Magazine, 9(4):35.Google Scholar
(2013). Testing and cognitive enhancement. Technical report, National Institute for Testing and Evaluation, Jerusalem.
and (2010). Working memory for patterned sequences of auditory objects in a songbird. Cognition, 117(1):38–53.Google Scholar
, , , , and (1998). Hierarchical complexity of tasks shows the existence of developmental stages. Developmental Review, 18(3):237–278.Google Scholar
A. and (2015). New and emerging models of human intelligence. Wiley Interdisciplinary Reviews: Cognitive Science, 6(5):419–426.Google Scholar
, , and (1997). Pigeon same–different concept learning with multiple stimulus classes. Journal of Experimental Psychology: Animal Behavior Processes, 23(4):417.Google Scholar
(2004). The essential Turing: Seminal writings in computing, logic, philosophy, artificial intelligence, and artificial life, plus the secrets of Enigma. Clarendon Press.
and (2008). Turing's test: A philosophical and historical guide. In , , and , editors, Parsing the Turing test: Philosophical and methodological issues in the quest for the thinking computer. Springer.
(2011). The recursive mind: The origins of human language, thought, and civilization. Princeton University Press.
and (1992). Four ways five factors are basic. Personality and Individual Differences, 13(6):653–665.Google Scholar
and (2005). Personality in adulthood: A five-factor theory perspective, second edition. Routledge.
(1926). The early mental traits of 300 geniuses. PhD thesis, Stanford University.
, , , , , , , , , , , , , , , , , , and (2006). An SCN9A channelopathy causes congenital inability to experience pain. Nature, 444(7121):894–898.Google Scholar
and (1995). Brain mechanisms in problem solving and intelligence: A replication and extension. Intelligence, 21(2):225–246.Google Scholar
DARPA(2015). Defense advanced research projects agency robotics challenge. http://www.theroboticschallenge.org/.
(1871). The descent of man, and selection in relation to sex. John Murray.
(2007). Socially intelligent robots: Dimensions of human–robot interaction. Philosophical Transactions of the Royal Society, Series, 362(1480):679–704.Google Scholar
(2014). The limitations of standardized science tests as benchmarks for artificial intelligence research: Position paper. CoRR arXiv preprint:1411.1629.
(2016). How to write science questions that are easy for people and hard for computers. AI Magazine, 37(1):13–22.Google Scholar
(1986). Problemy razvivayushego obucheniya (issues in developing learning). Pedagogika.
(2012). Animal suffering: The science of animal welfare. Springer Science and Business Media.
(1976). The selfish gene. Oxford University Press.
(2000). Unweaving the rainbow: Science, delusion and the appetite for wonder. Houghton Mifflin Harcourt.
and (1978). Animal signals: Information or manipulation. Behavioural Ecology: An Evolutionary Approach, 2:282–309.Google Scholar
(2009). Theory and practice of item response theory. Guilford Press.
(1785). Essais sur l'application de l'analyse à la probabilité des décisions rendues a la pluralité des voix. Paris.
(2013). The bonobo and the atheist. In search of humanism among the primates. W. W. Norton.
, , , , and (2002). Effects of cytotoxic hippocampal lesions in mice on a cognitive test battery. Behavioural Brain Research, 133(1):57–68.Google Scholar
, , , , , , , , and (2013). Donor/recipient enhancement of memory in rat hippocampus. Frontiers in Systems Neuroscience, 7:Article 120.
(2000a). Looking down on human intelligence: From psychometrics to the brain.
Oxford University Press.
(2000b). Simple information processing and intelligence. In , editor, Handbook of intelligence, pages 267–284. Cambridge University Press.
and (1997). Neuroscience and human intelligence differences. Trends in Neurosciences, 20(8):365–371.Google Scholar
, , and (2001). Reaction times and intelligence differences: A population-based cohort study. Intelligence, 29(5):389–399.Google Scholar
, , , , , and (1996). Intelligence and the differentiation hypothesis. Intelligence, 23(2):105–132.Google Scholar
, , and (1989). Evaluating research in cooperative distributed problem solving. Distributed Artificial Intelligence, 2:487–519.Google Scholar
, , , and (2006). Core knowledge of geometry in an Amazonian indigene group. Science, 311(5759):381–384.Google Scholar
and (2012). Numerical evaluation of algorithmic complexity for short strings: A glance into the innermost structure of randomness. Applied Mathematics and Computation, 219(1):63–77.Google Scholar
, , , , , and (2012). Interpersonal synchrony: A survey of evaluation methods across disciplines. IEEE Transactions on Affective Computing, 3(3):349–365.Google Scholar
, , and (2010). A theoretical framework to formalize AGI-Hard problems. In , , and (Eds.), 3rd Conference on Artificial General Intelligence, pages 178–179. Atlantis Press.
(1988). Conditions of personhood. In , editor, What is a person? Contemporary issues in biomedicine, ethics, and society, pages 145–167. Humana Press.
(1989). The intentional stance. MIT Press.
(1996). Kinds of minds: Toward an understanding of consciousness.
Basic Books.
(1991). Reply to Deary and Pagliari: Is g intelligence or stupidity. Intelligence, 15(2):251–255.Google Scholar
and (1989). Correlations of mental tests with each other and with cognitive variables are highest for low IQ groups. Intelligence, 13(4):349–359.Google Scholar
, , and (2000). Intelligence and mental retardation. In , editor, Handbook of intelligence, pages 141–158. Cambridge University Press.
(1985). Quantum theory, the Church-Turing principle and the universal quantum computer. Proceedings of the Royal Society of London, Series A, 400(1818):97–117.Google Scholar
(2012). How close are we to creating artificial intelligence? https://aeon.co/essays/how-close-are-we-to-creating-artificial-intelligence.
(2011). Learning what to value. In , , and (Eds.), 4th International Conference on Artificial General Intelligence, pages 309–314. Springer.
, , and (2014). Using sentiment to detect bots on Twitter: Are humans more opinionated than bots. In Advances in Social Networks Analysis and Mining (ASONAM), pages 620–627. IEEE.
, , , , , , , , , , et al.(2015). Acknowledging AI's dark side. Science, 349(6252):1064.Google Scholar
, , and (2014). The reinforcement learning competition 2014. AI Magazine, 35(3):61–65.Google Scholar
, , , et al.(2007). Towards a generic methodology for evaluating MAS performance. In International Conference on Integration of Knowledge Intensive Multi-Agent Systems, 2007 (KIMAS 2007), pages 174–179. IEEE.
and (1957). Some determinants of phenomenal overlapping. American Journal of Psychology, 70:21–37.Google Scholar
(2008). Foreword re C. S. Wallace. Computer Journal, 51(5):523–560. Christopher Stewart WALLACE (1933-2004) memorial special issue.Google Scholar
(2011). MML, hybrid Bayesian network graphical models, statistical consistency, invariance and uniqueness. In and , editors, Handbook of the philosophy of science, Volume 7: Philosophy of statistics, pages 901–982. Elsevier.
(2013). Introduction to Ray Solomonoff 85th memorial conference. In , editor, Algorithmic probability and friends: Bayesian prediction and artificial intelligence, pages 1–36. Lecture Notes in Computer Science, volume 7070. Springer.
and (1997). A computational extension to the Turing test. In Proceedings of the 4th Conference of the Australasian Cognitive Science Society, University of Newcastle, NSW, Australia.
and (1998). A non-behavioural, computational extension to the Turing Test. In International Conference on Computational Intelligence and Multimedia Applications (ICCIMA-98), Gippsland, Australia, pages 101–106.
and (2014). How universal can an intelligence test be. Adaptive Behavior, 22(1):51–69.Google Scholar
, , and (2011). Compression and intelligence: Social environments and communication. In , , and , editors, 4th International Conference on Artificial general intelligence, pages 204–211. Lecture Notes in Artificial Intelligence, volume 6830. Springer.
and (2006). Handbook of test development.
Lawrence Erlbaum Associates.
(1991). Made-up minds: A constructivist approach to artificial intelligence. MIT Press.
(1986). Engines of creation: The coming era of nanotechnology. Anchor Books.
and (2010). Warning: Statistical benchmarking is addictive. Kicking the habit in machine learning. Journal of Experimental and Theoretical Artificial Intelligence, 22(1):67–80.Google Scholar
(2011). Astrocognition: Prolegomena to a future cognitive history of exploration. In Humans in outer space: Interdisciplinary Perspectives, pages 117–140. Springer.
(2012). Peabody Picture Vocabulary Test, (PPVT-4). Pearson.
and (1990). MICE: A flexible testbed for intelligent coordination experiments. In , editor, Intelligent real time problem solving: Workshop report, pages X1–X16.
(1992). Sensory ecology. Freeman.
and (2013). A negative Flynn effect in Finland, 1997–2009. Intelligence, 41(6):817–820.Google Scholar
, , et al.(2008). Modeling transfer relationships between learning tasks for improved inductive transfer. In Machine learning and knowledge discovery in databases, pages 317–332. Springer.
(2016). The singularity controversy. Technical Report, STR 2016-1. doi:10.13140/RG.2.1.3416.6809.
, , , and (2012a). Singularity hypotheses: A scientific and philosophical assessment. Springer.
, , , and (2012b). Singularity hypotheses: An overview. In , , , and , editors, Singularity hypotheses, pages 1–12. Springer.
(2009). The social embedding of intelligence. In , , and , editors, Parsing the Turing test, pages 211–235. Springer.
, , , , , , and (2012). A large-scale model of the functioning brain. Science, 338(6111):1202–1205.Google Scholar
(1978). The rating of chessplayers, past and present, volume 3. Batsford.
(2004). The second century of ability testing: Some predictions and speculations. Measurement: Interdisciplinary Research and Perspectives, 2(1):1–32.Google Scholar
and S.(2000). Psychometric approaches to understanding and measuring intelligence. In , editor, Handbook of intelligence, pages 423–444. Cambridge University Press.
and (2000). Item response theory for psychologists. Lawrence Erlbaum Associates.
, , and (2007). Introduction. Social intelligence: from brain to culture. Philosophical Transactions of the Royal Society, Series B, 362(1480):485–488.Google Scholar
, , , , , , , , and (2015). Collective intelligence in computer-mediated collaboration emerges in different contexts and cultures. In Conference on Human Factors in Computing Systems, pages 3769–3778. ACM.
(1962). Augmenting human intellect: A conceptual framework. Summary Report, AFOSR-3233. Stanford Research Institute.
, , , and (1999). Working memory, short-term memory, and general fluid intelligence: A latent-variable approach. Journal of Experimental Psychology: General, 128(3):309.Google Scholar
, , and , editors(2008). Parsing the Turing test: Philosophical and methodological issues in the quest for the thinking computer. Springer.
and (1988). Maximum-entropy and Bayesian methods in science and engineering, volume 31. Springer Science and Business Media.
and (1969). GPS: A case study in generality and problem solving. Academic Press.
EU(2010). Directive 2010/63/EU of the European Parliament and of the Council of 22 september 2010 on the protection of animals used for scientific purposes. Official Journal of the European Union, 276:33–74.
and (2001). Performance metrics for intelligent systems. NIST Special Publication SP, pages 101–104.Google Scholar
and (2009). The myth of language universals: Language diversity and its importance for cognitive science. Behavioral and Brain Sciences, 32(05):429–448.Google Scholar
(1963). A heuristic program of solving geometric analogy problems. PhD thesis, MIT.
(1965). A heuristic program to solve geometric-analogy problems. In Proceedings Spring Joint Computer Conference, volume 25, pages 327–339. Spartan Books.
, , and (2014). Free lunch for optimisation under the universal distribution. In 2014 IEEE Congress on Evolutionary Computation (CEC), pages 167–174. IEEE.
(2007). The structure and measurement of intelligence. Transaction.
, , , , and (1985). Personality and individual differences: A natural science approach. Plenum.
and (1975). Manual of the Eysenck Personality Questionnaire (junior and adult). Hodder and Stoughton.
and (2010). Learning spaces: Interdisciplinary applied mathematics. Springer Science and Business Media.
and (2007). Personhood and neuroscience: Naturalizing or nihilating. American Journal of Bioethics, 7(1):37–48.Google Scholar
, , et al.(2003). Interspecies communication in bacteria. Journal of Clinical Investigation, 112(9):1291–1299.Google Scholar
, , and (1970). On generality and problem solving: A case study using the DENDRAL program. Stanford University.
, , and (2007). Benchmarks for evaluating socially assistive robotics. Interaction Studies, 8(3):423–439.Google Scholar
(2000). Minimization of boolean complexity in human concept learning. Nature, 407(6804):630–633.Google Scholar
(2003). Simplicity and complexity in human concept learning. The General Psychologist, 38(1):9–15.Google Scholar
and (2015). Rise of the machines: The effects of labor-saving innovations on jobs and wages. Centre for Economic Performance, London School of Economics and Political Science.
(2007). MacArthur-Bates Communicative Development Inventories: User's guide and technical manual. Paul H. Brookes.
, , and te (2014). Differences in cognitive abilities among primates are concentrated on g: Phenotypic and phylogenetic comparisons with two meta-analytical databases. Intelligence, 46:311–322.Google Scholar
, , and (2004). Metrics for finite Markov decision processes. In Proceedings of the 20th Conference on Uncertainty in Artificial Intelligence, pages 162–169. AUAI Press.
(2009). Difficulty, discrimination, and information indices in the linear factor analysis model for continuous item responses. Applied Psychological Measurement, 33(1):9–24.Google Scholar
(2012). Assessing the discriminating power of item and test scores in the linear factor-analysis model. Psicológica, 33:111–139.Google Scholar
, , , , and (2015). The rise of social bots. CoRR arXiv preprint:1407.5225.
, , , , , , , , , , et al.(2010). BuildingWatson: An overview of the DeepQA project. AI Magazine, 31(3):59–79.Google Scholar
and (2011). Ramon Llull: From the Ars Magna to artificial intelligence. Artificial Intelligence Research Institute, IIIA.
, , , , and (2008). Instrumental conditioning driven by apparently neutral stimuli: A model tested with a simulated robotic rat. In International Conference on Epigenetic Robotics: Modeling cognitive development in robotic systems, pages 13–20. IEEE.
(2004). Plant intelligence: An alternative point of view. Annals of Botany, 93(4):345–351.Google Scholar
(1980). A theory of cognitive development: The control and construction of hierarchies of skills. Psychological Review, 87(6):477.Google Scholar
(2012). Machine learning: The art and science of algorithms that make sense of data. Cambridge University Press.
(1979). Humanhood: Essays in biomedical ethics. Prometheus Books.
, , , , , and (2011). Comparing machines and humans on a visual categorization test. Proceedings of the National Academy of Sciences, 108(43):17621–17625.Google Scholar
(2013). The ethics of information. Oxford University Press.
(2007). What is intelligence? Beyond the Flynn effect. Cambridge University Press.
(1983). The modularity of mind: An essay on faculty psychology. MIT Press.
and (1995). Challenging the “law of diminishing returns”. Intelligence, 21(2):157–174.Google Scholar
(1995). Evolutionary computation: Toward a new philosophy of machine intelligence. IEEE.
and (1998). On computational wings: Rethinking the goals of artificial intelligence – the gold standard of traditional artificial intelligence – passing the so-called Turing test and thereby appearing to be. Scientific American, 9(Winter):78–83.Google Scholar
(2006). The structure of sequential behavior. In and , editors, Comparative cognition: Experimental explorations of animal intelligence, pages 439–458. Oxford University Press.
and (1859). Self-instructor in phrenology and physiology. Fowler and Wells.
, , , and (2003). Strategic navigation of two-dimensional alley mazes: Comparing capuchin monkeys and chimpanzees. Animal Cognition, 6:149–160.Google Scholar
, , , , , , and (2009). Navigating two-dimensional mazes: Chimpanzees (Pan troglodytes) and capuchins (Cebus apella sp.) profit from experience differently. Animal Cognition, 12(3):491–504.Google Scholar
(1971). Freedom of the will and the concept of a person. Journal of Philosophy, 68(1):5–20.Google Scholar
(2000). The Turing test: The first 50 years. Trends in Cognitive Sciences, 4(3):115–122.Google Scholar
and (2013). The future of employment: How susceptible are jobs to computerisation?
University of Oxford.
and (2010). The social brain: Allowing humans to boldly go where no other species has been. Philosophical Transactions of the Royal Society of London, Series B, 365(1537):165–176.Google Scholar
, , and (2015). Prediction as a humanitarian and pragmatic contribution from human cognitive neuroscience. Neuron, 85(1):11–26.Google Scholar
and (2011). Raymond J. Solomonoff 1926–2009. IEEE Information Theory Society Newsletter, 61(1):11–16.Google Scholar
(2005). A census of membrane-bound and intracellular signal transduction proteins in bacteria: Bacterial IQ, extroverts and introverts. BMC Microbiology, 5(1):35.Google Scholar
(1869). Hereditary genius: An Inquiry into its laws and consequences, 3rd edition 1892. Macmillan.
(1883). Inquiries into the human faculty and its development. Macmillan.
(1906). Cutting a round cake on scientific principles (letters to the editor). Nature, 75(1938):173.Google Scholar
(2013). Asume que no es humano al ser incapaz de reconocer un código CAPTCHA. El Mundo Today. http://www.elmundotoday.com/2013/03/asume-que-no-es-humano-al-ser-incapaz-de-reconocer-un-codigo-captcha/.
(1983). Frames of mind: The theory of multiple intelligences. Basic Books.
, , and (2015). The information-theoretic and algorithmic approach to human, animal and artificial cognition. CoRR arXiv preprint:1501.04242.
(2013). A measure of real-time intelligence. Journal of Artificial General Intelligence, 4(1):31–48.Google Scholar
, & (2006). Conceptual development. In & (Eds.), Handbook of child psychology, Vol. 2: Cognition, perception and language. pages 687–733. John Wiley.
, , and (2005). General game playing: Overview of the AAAI competition. AI Magazine, 26(2):62.Google Scholar
and (2014). General game playing. Synthesis Lectures on Artificial Intelligence and Machine Learning, 8(2):1–229.Google Scholar
, , , and (2006). Recursive syntactic pattern learning by songbirds. Nature, 440(7088):1204–1207.Google Scholar
and (1987). The effect of amodal completion on visual matching. Acta Psychologica, 65(1):25–46.Google Scholar
and (2014). Datasets and benchmarking. In Vision-based pedestrian protection systems for intelligent vehicles, pages 87–93. Springer.
(1984). Neuromancer. Penguin.
(1993). Essentials of artificial intelligence. Newnes.
and (2009). Epigenetic learning in non-neural organisms. Journal of Biosciences, 34(4):633–646.Google Scholar
(1963). Instructional technology and the measurement of learing outcomes: Some questions. American Psychologist, 18(8):519.Google Scholar
(1974). The Yerkish language for non-human primates. American Journal of Computational Linguistics, 1.Google Scholar
(2006). The hidden pattern. Brown Walker.
(2010). Toward a formal characterization of real-world general intelligence. In , , and , editors, 3rd International Conference on Artificial General Intelligence, pages 19–24. Atlantis Press.
, , and (2010). Cogbot: An integrative cognitive architecture aimed at emulating early childhood intelligence in a humanoid robot. http://www.goertzel.org/CogBot_public.pdf.
, , and (2009). Toward a roadmap for human-level artificial general intelligence: Embedding HLAI systems in broad, approachable, physical or virtual contexts. Artificial General Intelligence Roadmap Initiative.
and (2009). AGI preschool: A framework for evaluating earlystage human-like AGIs. In the 2nd International Conference on Artificial General Intelligence (AGI-09), pages 31–36. Atlantis Press.
and , editors(2007). Artificial general intelligence. Springer.
, , , and (2011). Predicting personality from Twitter. In Privacy, security, risk and trust: 2011 IEEE Third International Conference on Social Computing (socialcom), pages 149–156. IEEE.
, , , , , , and (2006). The international personality item pool and the future of public-domain personality measures. Journal of Research in Personality, 40(1):84–96.Google Scholar
, , and (2006). Interactive computation. Springer.
and (2007). Special issue on worst-case versus average-case complexity – editors' foreword. Computational Complexity, 16(4):325–330.Google Scholar
(2007). Social intelligence. Random House.
(1965). Speculations concerning the first ultraintelligent machine. Advances in Computers, 6(99):31–83.Google Scholar
(1971). Twenty-seven principles of rationality. In Foundations of statistical inference, page 197. Holt, Rinehart, Winston.
(2007). Report on panel discussion on (re-)establishing or increasing collaborative links between artificial intelligence and intelligent systems. In and , editors, Proceedings of the 2007 Workshop on Performance Metrics for Intelligent Systems, pages 302–303. NIST.
(2001). From mice to men: What can we learn about personality from animal research. Psychological Bulletin, 127(1):45.Google Scholar
and (1999). Personality dimensions in nonhuman animals a cross-species review. Current Directions in Psychological Science, 8(3):69–75.Google Scholar
(1997a). Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography. Intelligence, 24(1):13–23.Google Scholar
(1981). The mismeasure of man, revised and expanded edition. W. W. Norton.
(1959). La reconstruction du nid et les coordinations interindividuelles chez bellicositermes natalensis et cubitermes sp. la théorie de la stigmergie: Essai d'interprétation du comportement des termites constructeurs. Insectes sociaux, 6(1):41–80.Google Scholar
, , , , , , and (2008). Towards responsible use of cognitive-enhancing drugs by the healthy. Nature, 456(7223):702–705.Google Scholar
(1954). The abilities of babies: A study in mental measurement.
McGraw- Hill.
, , and (1999). Measuring memory span. International Journal of Psychology, 34(5–6):359–363.Google Scholar
and (2004). Teaching intelligence: A performance conception. In , editor, Handbook of intelligence, pages 492–518. Cambridge University Press.
, , and , editors(2005). Advances in minimum description length: Theory and applications. MIT Press.
(1982). Cognitive psychology's ambiguities: Some suggested remedies. Psychological Review, 89(1):48.Google Scholar
(1967). The nature of human intelligence. McGraw-Hill.
(1945). The relation of item difficulty and inter-item correlation to test variance and reliability. Psychometrika, 10(2):79–91.Google Scholar
, , , , , and (2015). Inductive programming meets the real world. Communications of the ACM, 58(11):90–99.Google Scholar
(2012). The machine question: Critical perspectives on AI, robots, and ethics. MIT Press.
(2014). A vindication of the rights of machines. Philosophy and Technology, 27(1):113–132.Google Scholar
(1954). A new approach to factor analysis: The Radex. Free Press.
(2007). Beyond AI: Creating the conscience of the machine. Prometheus Books.
(2013). Measurements of collective machine intelligence. CoRR arXiv preprint:1306.6649.
, , and (2010). Towards a philosophy of the web: Representation, enaction, collective intelligence. Web Science Conference.
(1859). Lectures on metaphysics and logic, volume 1. Gould and Lincoln.
and (2008). Test of language development – intermediate (TOLD I: 3). Pro-Ed.
, , , , , , , , , , et al.(2012). A nonlinear model for hippocampal cognitive prosthesis: Memory facilitation by hippocampal ensemble stimulation. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 20(2):184–197.Google Scholar
, , , , , , , , and (2013). Facilitation of memory encoding in primate hippocampus by a neuroprosthesis that promotes task-specific neural firing. Journal of Neural Engineering, 10(6):066013.Google Scholar
(2004). Measurement theory and practice. Hodder Arnold.
(1969). Classical conditioning of a plant: Mimosa pudica. Journal of Biological Psychology, 11:5–12.Google Scholar
, , and (1993). Benchmarks, test beds, controlled experimentation, and the design of agent architectures. AI Magazine, 14(4): 17.Google Scholar
, , , and (2011). Comparing the performances of apes (Gorilla gorilla, Pan troglodytes, Pongo pygmaeus) and human children (Homo sapiens) in the floating peanut task. PloS ONE, 6(6):e19555.Google Scholar
(1991). Simians, cyborgs, and women: The reinvention of nature. Routledge.
and (1995). Problem difficulty and response format in syllogistic reasoning. Quarterly Journal of Experimental Psychology, 48(4):945–975.Google Scholar
and (2005). Human-like social skills in dogs. Trends in Cognitive Sciences, 9(9):439–444.Google Scholar
(1992). The Turing Test is not a trick: Turing indistinguishability is a scientific criterion. ACM SIGART Bulletin, 3(4):9–10.Google Scholar
, et al.(1977). Population biology of plants.
Academic Press.
and (2004). A test of Spearman's “law of diminishing returns” in two large samples of Danish military draftees. Intelligence, 32(5):499–508.Google Scholar
and (2015). When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span. Psychological Science, 26(4):433–443.Google Scholar
, , and (2007). Evolutionary linguistics: A new look at an old landscape. Language Learning and Development, 3(2):101–132.Google Scholar
, , and (2002). The faculty of language: What is it, who has it, and how did it evolve. Science, 298(5598):1569–1579.Google Scholar
(2013). On the way to intelligence singularity. In Beyond artificial intelligence, pages 3–26. Springer.
(2002). Computing science: The easiest hard problem. American Scientist, pages 113–117.Google Scholar
and (1995). Turing test considered harmful. In International Joint Conference on Artificial Intelligence (IJCAI), pages 972–977. IJCAI.
(1988). Dynamic assessment: The learning potential assessment device. In (Ed.), Psychoeducational assessment of minority group children: A casebook, pages 39–63. Cobb and Henry.
, , , and (2007). Anote on problem difficulty measures in black-box optimization: Classification, realizations and predictability. Evolutionary Computation, 15(4):435–443.Google Scholar
, , and (2010). The weirdest people in the world. Behavioral and Brain Sciences, 33(2–3):61–83.Google Scholar
, , , and (2015). Mammalian brains are made of these: A dataset of the numbers and densities of neuronal and nonneuronal cells in the brain of glires, primates, scandentia, eulipotyphlans, afrotherians and artiodactyls, and their relationship with body mass. Brain, Behavior, and Evolution, 86(3–4):145–163.Google Scholar
, , , , , , and (2015). Teaching machines to read and comprehend. CoRR arXiv preprint:1506.03340.
, , and (2009). Assessment of sign language development: The case of deaf children in the Netherlands. Journal of Deaf Studies and Deaf Education, 15(2):107–119.Google Scholar
(1999a). Computational measures of information gain and reinforcement in inference processes. PhD thesis, Department of Logic and Philosophy of Science, University of Valencia. http://users.dsic.upv.es/∼jorallo/tesi/.
(1999b). Universal and cognitive notions of part. In , et al., editor, Proceedings of 4th Systems Science European Congress, pages 711–722. Sociedad Espanola de Sistemas Generales.
(2000a). Beyond the Turing test. Journal of Logic, Language, and Information, 9(4):447–466.Google Scholar
(2000c). Constructive reinforcement learning. International Journal of Intelligent Systems, 15(3):241–264.Google Scholar
(2000d). On the computational measurement of intelligence factors. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 72–79. NIST Special Public. (2000d). On the computational measurement of intelligence factors. In Meystel, A.M. and Messina|E.R., editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 72–79. NIST Special Publication 970. NIST.
(2000e). Thesis: Computational measures of information gain and reinforcement in inference processes. AI Communications, 13(1):49–50.Google Scholar
(2010). A (hopefully) non-biased universal environment class for measuring intelligence of biological and artificial systems. In , , and , editors, Third International Conference on Artificial General Intelligence, pages 182–183. Atlantis Press.
(2015a). C-tests revisited: Back and forth with complexity. In , , and , editors, Artificial General Intelligence – 8th International Conference, AGI 2015, Berlin, Germany, July 22–25, 2015, Proceedings, pages 272–282. Springer.
(2015b). A note about the generalisation of the C-tests. arXiv preprint:1412.8529.
(2015c). On environment difficulty and discriminating power. Autonomous Agents and Multi-Agent Systems, 29:402–454.Google Scholar
(2015d). Stochastic tasks: Difficulty and Levin search. In , , and , editors, Artificial General Intelligence – 8th International Conference, AGI 2015, Berlin, Germany, July 22–25, 2015, Proceedings, pages 90–100. Springer.
(2015e). Universal psychometrics tasks: Difficulty, composition and decomposition. arXiv preprint:1503.07587.
(2016). Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement. Artificial Intelligence Review. doi: http://dx.doi.org/ 10.1007/s10462-016-9505-7.
and (2010). Measuring universal intelligence: Towards an anytime intelligence test. Artificial Intelligence, 174(18):1508–1539.Google Scholar
and (2013). On potential cognitive abilities in the machine kingdom. Minds and Machines, 23:179–210.Google Scholar
, , , , and (2011). On more realistic environment distributions for defining, evaluating and developing intelligence. In , , and , editors, 4th International Conference on Artificial general intelligence, pages 82–91. Lecture Notes in Artificial Intelligence, volume 6830. Springer.
, , and (2014). Universal psychometrics: Measuring cognitive abilities in the machine kingdom. Cognitive Systems Research, 27:50–74.Google Scholar
and (2000). Explanatory and creative alternatives to the MDL principle. Foundations of Science, 5(2):185–207.Google Scholar
, , , and (2012). Turing tests with Turing machines. In , editor, Turing-100, volume 10, pages 140–156. EPiC Series.
, , , , and (2016). Computer models solving human intelligence test problems: Progress and implications. Artificial Intelligence, 230:74–107.Google Scholar
and (1998). A formal definition of intelligence based on an intensional variant of Kolmogorov complexity. In Proceedings of the International Symposium of Engineering of Intelligent Systems (EIS-98), pages 146–163. ICSC Press.
and (2012). Are there geniuses among the apes. Philosophical Transactions of the Royal Society, Series B, 367(1603):2753–2761.Google Scholar
, , , , and (2007). Humans have evolved specialized skills of social cognition: The cultural intelligence hypothesis. Science, 317(5843):1360–1366.Google Scholar
, , , , and (2010). The structure of individual differences in the cognitive abilities of children and chimpanzees. Psychological Science, 21(1):102.Google Scholar
, , , and (2015). Uniquely human self-control begins at school age. Developmental Science, 18(6):979–993.Google Scholar
and (1994). Bell curve: Intelligence and class structure in American life. Simon and Schuster.
(2014). Profiling nonhuman intelligence: An exercise in developing unbiased tools for describing other “types” of intelligence on Earth. Acta Astronautica, 94(2):676–680.Google Scholar
(2011). Conceptions of a global brain: An historical review. In , , , and , editors, Evolution: Cosmic, biological, and social, pages 274–289. Uchitel.
(2002). Humans will want to become super-intelligent machines. In Superintelligent machines, pages 193–198. Springer.
(2008). Adversarial sequence prediction. Frontiers in Artificial Intelligence and Applications, 171:399.Google Scholar
(2009). Bias and no free lunch in formal measures of intelligence. Journal of Artificial General Intelligence, 1(1):54–61.Google Scholar
(2011). Measuring agent intelligence via hierarchies of environments. In , , and , editors, 4th International Conference on Artificial general intelligence, pages 303–308. Lecture Notes in Artificial Intelligence, volume 6830. Springer.
(2015a). Bill Hibbard on ethical artificial intelligence, an interview by Luke Muehlhauser. Machine Intelligence Research Institute.
(2015b). Ethical artificial intelligence. CoRR arXiv preprint:1411.1373.
(2010). A new design for a Turing test for bots. In 2010 IEEE Symposium on Computational Intelligence and Games (CIG), pages 345–350. IEEE.
(2012). Believable bots: Can computers play like people?
Springer.
and (2002). Complexity measures of supervised classification problems. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(3):289–300.Google Scholar
, , , , and La (2005). An overview of cooperative and competitive multiagent learning. In International Conference on Learning and Adaption in Multi-Agent Systems, pages 1–46. Springer.
(2013). Language development. Cengage Learning.
(1979). Gödel, Escher, Bach: An eternal golden braid. Basic Books.
(2007). Questioning the social intelligence hypothesis. Trends in Cognitive Sciences, 11(2):65–69.Google Scholar
(2014). The Oxford handbook of language and social psychology. Oxford University Press.
, , and (2013). Benchmarking intelligent service robots through scientific competitions: The RoboCup@Home approach. In AAAI Spring Symposium: Designing Intelligent Robots, pp. 27–32. Association for the Advancement of Artificial Intelligence.
and (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. Proceedings of the National Academy of Sciences of the United States of America, 101(46):16385–16389.Google Scholar
(1999). SAT-encodings, search space structure, and local search performance. In International Joint Conference on Artificial Intelligence (IJCAI), volume 99, pages 296–303. IJCAI.
, , and (2007). Introduction to automata theory, languages, and computation, 3rd edition. Pearson.
and (1967). Age differences in fluid and crystallized intelligence. Acta Psychologica, 26:107–129.Google Scholar
, , and (2009). Testing the effectiveness of discrete and continuous environmental diversity as a surrogate for species diversity. Ecological Indicators, 9(1):138–149.Google Scholar
(2008). Crowdsourcing: How the power of the crowd is driving the future of business. Random House.
(1575). Examen de los ingenios para las sciencias. English translation by Richard Carew “The examination of men's wits”, new edition by Rocío G. Sumillera, Modern Humanities Research Association, 2014.
Humies (2004). Humies awards. www.human-competitive.org, http://www.geneticprogramming.org/combined.php.
(1976). The social function of intellect. In and , editors, Growing points in ethology, pages 303–317. Cambridge University Press.
(2011). The role of the unit in physics and psychometrics – and rejoinder. Measurement, 9(1):1–24, 64–70.Google Scholar
(1928). The measurement of social intelligence. Journal of Applied Psychology, 12(3):317.Google Scholar
(2002). The fastest and shortest algorithm for all well-defined problems. International Journal of Foundations of Computer Science, 13:431–443.Google Scholar
(2005). Universal artificial intelligence: Sequential decisions based on algorithmic probability. Springer.
(2007). Universal algorithmic intelligence: A mathematical top→down approach. In and , editors, Artificial general intelligence, cognitive technologies, pages 227–290. Springer.
(2012a). Can intelligence explode. Journal of Consciousness Studies, 19(1– 2):143–166.Google Scholar
(2012b). One decade of universal artificial intelligence. In Theoretical foundations of artificial general intelligence, pages 67–88. Springer.
and (2005). A no-free-lunch theorem for non-uniform distributions of target functions. Journal of Mathematical Modelling and Algorithms, 3(4):313–322.Google Scholar
and (2007). Working memory of numerals in chimpanzees. Current Biology, 17(23):R1004–R1005.Google Scholar
(2016). Towards a universal test of social intelligence. PhD thesis, Universitat Politecnica de Valencia.
, , and (2012a). On measuring social intelligence: Experiments on competition and cooperation. In , , and , editors, 5th International Conference on Artificial General Intelligence, pages 126–135. Lecture Notes in Computer Science, volume 7716. Springer.
, , , , and (2011a). Comparing humans and AI agents. In , , and , editors, 4th International Conference on Artificial general intelligence, pages 122–132. Lecture Notes in Artificial Intelligence, volume 6830. Springer.
, , and (2011b). Evaluating a reinforcement learning algorithm with a general intelligence test. In , , and , editors, Current Topics in Artificial Intelligence:CAEPIA 2011. Lecture Notes in Artificial Intelligence, volume 7023, pages 1–11. Springer.
and (2014). Definition and properties to assess multi-agent environments as social intelligence tests. CoRR arxiv preprint: abs/1408.6350.
, , , , and (2012b). The anYnt project intelligence test : Lambda – one. In and , editors, AISB/IACAP 2012 Symposium “Revisiting Turing and His Test”, pages 20–27. Society for the Study of Artificial Intelligence and the Simulation of Behaviour.
, , , , , , and (2006). Experimental study on task teaching to real rats through interaction with a robotic rat. In From animals to animats 9, pages 643–654. Springer.
, , , , and (2005). Understanding of the concept of numerically ‘less’ by bottlenose dolphins (tursiops truncatus). Journal of Comparative Psychology, 119(3):296.Google Scholar
, , , , and (2003). Test arenas and performance metrics for urban search and rescue robots. In Intelligent Robots and Systems, 2003 (IROS 2003), volume 4, pages 3396–3403. IEEE.
, , , and (2000). A hierarchical IRT model for criterion-referenced measurement. Journal of Educational and Behavioral Statistics, 25(3):285–306.Google Scholar
and (2011). Evaluating learning algorithms. Cambridge University Press.
(2010). El Ars Generalis ultima de Ramon Llull: Presupuestos metafísicos y éticos. Anales del Seminario de Historia de la Filosofía, 27:87–113.Google Scholar
, , , , and (2014). Using the Aesop's fable paradigm to investigate causal understanding of water displacement by new Caledonian crows. PloS ONE, 9(3):e92895.Google Scholar
(1980). Chronometric analysis of intelligence. Journal of Social and Biological Structures, 3(2):103–122.Google Scholar
(1993). Why is reaction time correlated with psychometric g. Current Directions in Psychological Science, 2(2):53–56.Google Scholar
(1998). The g factor: The science of mental ability. Praeger.
(2000a). Artificial intelligence and g theory concern different phenomena. Psycoloquy, 11(86), Article 47.Google Scholar
(2000b). A nihilistic philosophy of science for a scientific psychology. Psycoloquy, 11(88): Article 49.Google Scholar
(2003). Regularities in Spearman's law of diminishing returns. Intelligence, 31(2):95–105.Google Scholar
, , and (2008). Paradigm shift to the integrative big five trait taxonomy. In Handbook of personality: Theory and research, 3rd edition, pages 114–158. Guilford Press.
, , , and (2016). The Malmo platform for artificial intelligence experimentation. In International Joint Conference on Artificial Intelligence (IJCAI), pages 4246–4247. IJCAI.
and (2011). Guttman, Louis in Leading personalities in statistical sciences: from the seventeenth century to the present, pp. 112–117, John Wiley.
(1986). Mental models. Harvard University Press.
, , and (2015). Logic, probability, and human reasoning. Trends in Cognitive Sciences, 19(4):201–214.Google Scholar
and (2011). Evaluating integrated, knowledge-rich cognitive systems. In AAAI Fall Symposium: Advances in Cognitive Systems, pages 138–145. Association for the Advancement of Artificial Intelligence.
, , , and (2013). What you do is who you are: The role of task context in perceived social robot personality. In 2013 IEEE International Conference on Robotics and Automation (ICRA), pages 2134–2139. IEEE.
(2011). A review of literature on the general factor of personality. Personality and Individual Differences, 50(6):765–771.Google Scholar
(2000). Grading intelligence in machines: Lessons from animal intelligence. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 331–334. NIST Special Publication 970. NIST.
, , and (2012). Combining human and machine intelligence in large-scale crowdsourcing. In Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, volume 1, pages 467–474. International Foundation for Autonomous Agents and Multiagent Systems.
, , , and (2003). Performance competitions as research infrastructure: Large scale comparative studies of multi-agent teams. Autonomous Agents and Multi-Agent Systems, 7(1–2):121–144.Google Scholar
(2005). Clinical assessment of child and adolescent intelligence. Springer Science and Business Media.
and (2005). Clinical assessment of child and adolescent personality and behavior. Springer Science and Business Media.
and (1991). Where the really hard problems are. In International Joint Conference on Artificial Intelligence (IJCAI), volume 91, pages 163–169. IJCAI.
(1785). Grundlegung zur Metaphysik der Sitten. Hartknoch, Riga, German- English edition “Groundwork of the Metaphysics ofMorals”, edited and translated by Mary Gregor and Jens Timmermann, 2011.
, , , , and Sheth, S.A.(2013). Deep brain stimulation: A mechanistic and clinical update. Neurosurgical Focus, 35(5):E1.Google Scholar
, , and (2012). Believable bot navigation via playback of human traces. In , editor, Believable bots, pages 151–170. Springer.
(2010). Towards a staged developmental intelligence test for machines. In Towards a Comprehensive Intelligence Test (TCIT): Reconsidering the Turing Test for the 21st Century Symposium, pages 28–32. Society for the Study of Artificial Intelligence and Simulation of Behaviour.
and (2010). Cattell–Horn–Carroll abilities and cognitive tests: What we've learned from 20 years of research. Psychology in the Schools, 47(7):635–650.Google Scholar
(1927). Interpretation of educational measurements.
World Book.
(1928). Crossroads in the mind of man: A study of differentiable mental abilities.
Stanford University Press.
and (2001). The structure of verbal abilities in young and older adults. Psychology and Aging, 16(2):312.Google Scholar
and (2012). Competitive benchmarking: Lessons learned from the trading agent competition. AI Magazine, 33(2):103.Google Scholar
(1931). Essays in persuasion. Macmillan.
and (2000). Social intelligence. In , editor, Handbook of intelligence, pages 359–379. Cambridge University Press.
(2006). Task difficulty as a predictor and indicator of web searching interaction. In CHI-06 Extended Abstracts on Human Factors in Computing Systems, pages 959–964. ACM.
, , , and (2004). Soccer robotics. Springer.
and (1997). The five-factor model plus dominance in chimpanzee personality. Journal of Research in Personality, 31(2):257–271.Google Scholar
, , , , and (1997). Robocup: The robot world cup initiative. In International Conference on Autonomous Agents, pages 340–347. International Foundation for Autonomous Agents and Multiagent Systems.
, , , , , , , and (2013). The future of crowd work. In Proceedings of the 2013 Conference on Computer Supported Cooperative Work, pages 1301–1318. ACM.
, , and (2012). Robots in the service of animal behavior. Communicative and Integrative Biology, 5(5):466–472.Google Scholar
(2011). Who are you calling bird-brained? An attempt is being made to devise a universal intelligence test. The Economist, 398(8723):82.Google Scholar
, , , and (2011). Using analogical model formulation with sketches to solve Bennett mechanical comprehension test problems. Journal of Experimental and Theoretical Artificial Intelligence, 23(3):299–327.Google Scholar
(1998). The new psychometrics: Science, psychology and measurement. Routledge.
(2000). Handbook of psychological testing, 2nd edition. Routledge.
(1973). Sorting and searching, volume 3 of The art of computer programming. Addison-Wesley.
(1941). Vom Erlernen unbenannter Anzahlen bei Vögeln. Naturwissenschaften, 29(14):201–218.Google Scholar
(2012). Embracing competitive balance: The case for substrateindependent minds andwhole brain emulation. In , , , and , editors, Singularity hypotheses, pages 241–267. Springer.
(1996). Creating the kingdom of ends. Cambridge University Press.
, , , , and (2012). Crowd IQ: Measuring the intelligence of crowdsourcing platforms. In Proceedings of the 4th Annual ACM Web Science Conference, pages 151–160. ACM.
, , and (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15):5802–5805.Google Scholar
, editor(2012). The big bang theory and philosophy: Rock, paper, scissors, Aristotle, Locke. John Wiley.
(2010). Human-competitive results produced by genetic programming. Genetic Programming and Evolvable Machines, 11(3–4):251–284.Google Scholar
, , and (2011a). Interactive robots in experimental biology. Trends in Ecology and Evolution, 26(7):369–375.Google Scholar
, , , , and (2011b). Swarm intelligence in humans: diversity can trump ability. Animal Behaviour, 81(5):941–948.Google Scholar
and (1980). On the psychology of structural simplicity. In and , editors, The nature of thought: Essays in honor of D. O. Hebb, pages 187–205. Psychology Press.
, , and .(2007). Comparative social cognition: From wolf and dog to humans. Comparative Cognition and Behavior Reviews, 2:26–46.Google Scholar
(1939). Tests of mental development: A complete scale for individual examination. Educational Test Bureau, Educational Publishers.
(2004). Combining pattern classifiers: Methods and algorithms. John Wiley.
(2005). The singularity is near:When humans transcend biology. Penguin.
, , and (2013). Formalizing the construction of populations in multi-agent simulations. Engineering Applications of Artificial Intelligence, 26(1):211–226.Google Scholar
(2012). The Soar cognitive architecture. MIT Press.
, , and (1987). Soar: An architecture for general intelligence. Artificial Intelligence, 33(1):1–64.Google Scholar
and (2010). Cognitive architecture requirements for achieving AGI. In , , and , editors, Proceedings of the 3rd International Conference AGI, Artificial general intelligence, pages 79–84. Advances in Intelligent Systems Research. Atlantis Press.
,, , and (2009). Claims and challenges in evaluating human-level intelligent systems. In the Second Conference on Artificial General Intelligence, pages 91–96. Atlantis Press.
, , and (2015). Human-level concept learning through probabilistic program induction. Science, 350(6266):1332–1338.Google Scholar
and (2014). Tracking the digital footprints of personality. Proceedings of the IEEE, 102(12):1934–1939.Google Scholar
(2005). Clever methods of overfitting. Machine Learning (Theory). http://hunch.net/?p=22.
, , and (2009). Metrics for multiagent systems. In Performance evaluation and benchmarking of intelligent systems, pages 1–19. Springer.
(1901). The ‘Universal Library’. Originally in “Traumkristalle”, English translation in “Fantasia mathematica”, Clifton Fadiman, 1958, translated by Willy Ley, pp. 237–243.
(2013). Theory of general reinforcement learning. PhD thesis, Australian National University.
and (2013). No free lunch versus Occam's razor in supervised learning. In , editor, Algorithmic probability and friends: Bayesian prediction and artificial intelligence, pages 223–235. Lecture Notes in Computer Science, volume 7070. Springer.
(2011). Group problem solving. Princeton University Press.
and Von (2011). Human computation. Synthesis Lectures on Artificial Intelligence and Machine Learning, 5(3):1–121.Google Scholar
, , and (2000). Measure of system intelligence: An engineering perspective. In
, editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 112–117. NIST Special Publication 970. NIST.
(1969). Quantitative specification of information in sequential patterns. Psychological Review, 76(2):216.Google Scholar
and (2012). Structural information theory: The simplicity of visual form. Cambridge University Press.
(2008). Machine super intelligence. PhD thesis, Department of Informatics, University of Lugano.
and (2005). A universal measure of intelligence for artificial agents. In International Joint Conference on Artificial Intelligence, IJCAI, pages 1509–1510. IJCAI.
and (2007a). A collection of definitions of intelligence. Frontiers in Artificial Intelligence and Applications, 157:17.Google Scholar
and (2007b). Tests of machine intelligence. In , , , and , editors, 50 Years of Artificial Intelligence, pages 232–242. Lecture Notes in Computer Science, volume 4850. Springer.
and (2007c). Universal intelligence: A definition of machine intelligence. Minds and Machines, 17(4):391–444.Google Scholar
and (2013). An approximation of the universal intelligence measure. In , editor, Algorithmic probability and friends: Bayesian prediction and artificial intelligence, pages 236–249. Lecture Notes in Computer Science, volume 7070. Springer.
(1985). Can animals and machines be persons? A dialogue. Hackett.
and (2015). Bad universal priors and notions of optimality. JMLR: Workshop and Conference Proceedings, 40:1–16.Google Scholar
(1971). The Futurological Congress (from the memoirs of Ijon Tichy). Translated into English in 1974 by Michael Kandel. Seabury Press.
, , and (2012). The Winograd schema challenge. In Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning, pages 552–561.Google Scholar
(1973). Universal sequential search problems. Problems of Information Transmission, 9(3):265–266.Google Scholar
(1974). Laws of information conservation (nongrowth) and aspects of the foundation of probability theory. Problemy Peredachi Informatsii (Problems of Information Transmission), 10(3):30–35.Google Scholar
(2013).Universal heuristics: Howdo humans solve “unsolvable” problems? In , editor, Algorithmic probability and friends: Bayesian prediction and artificial intelligence, pages 53–54. Lecture Notes in Computer Science, volume 7070. Springer.
, , , , , , , , , , et al.(2013). General video game playing. Artificial and Computational Intelligence in Games, 6:77–83.Google Scholar
and (2012). The new division of labor: How computers are creating the next job market. Princeton University Press.
and (2008). An introduction to Kolmogorov complexity and its applications (3rd edition). Springer.
and (2008). A faceted approach to conceptualizing tasks in information seeking. Information Processing and Management, 44(6):1822–1837.Google Scholar
, , , and (2001). Method for selectively restricting access to computer systems. Filed on 13 April 1998 and granted on 27 February 2001, US Patent 6,195,698.
and (2009). Judgment aggregation: A survey. In , , (Eds.) Rational and Social Choice, pages 457–482. Oxford University Press.
and (1972). Potential intelligence or intelligence test potential? A question of empirical validity. Journal of Consulting and Clinical Psychology, 39(1):168.Google Scholar
, , , and (2012). Motif difficulty (MD): A predictive measure of problem difficulty for evolutionary algorithms using network motifs. Evolutionary Computation, 20(3):321–347.Google Scholar
, , , and (2010). Predicting task difficulty for different task types. Proceedings of the American Society for Information Science and Technology, 47(1):1–10.Google Scholar
and (2012). Task complexity: A review and conceptualization framework. International Journal of Industrial Ergonomics, 42(6):553–568.Google Scholar
(2006). Item analysis. In and , editors, Handbook of test development, pages 421–441. Lawrence Erlbaum Associates.
(1295). Cant de Ramon. Lo desconhort. Ensiola Editorial, 2006.
(1305). Ars generalis ultima. Edition by Alois Madre, ROL XIV. Turnhout.
(2008). How to hold a Turing test contest. In , , and , editors, Parsing the Turing test: Philosophical and methodological issues in the quest for the thinking computer, pages 173–179. Springer.
(2000). Group differences in intelligence. In , editor, Handbook of intelligence, pages 176–193. Cambridge University Press.
(2014). Visuo-spatial working memory. Psychology Press.
(2000). Complex information processing and intelligence. In , editor, Handbook of intelligence, pages 285–340. Cambridge University Press.
, , , and (2011). Reasoning and intelligence. In , editor, Handbook of intelligence, pages 419–441. Cambridge University Press.
and (2003). The 3rd international planning competition: Results and analysis. Journal of Artificial Intelligence Research, 20:1–59.Google Scholar
and (2012). Why an intelligence explosion is probable. In , , , and , editors, Singularity hypotheses, pages 83–98. Springer.
, , and (1968). Statistical theories of mental test scores.
Addison-Wesley.
and (2011). Cultural commonalities and differences in spatial problem-solving: A computational analysis. Cognition, 121(2):281–287.Google Scholar
, , and (2010). A structure-mapping model of Raven's Progressive Matrices. In Proceedings of the 32nd Annual Conference of the Cognitive Science Society, volume 10, pages 2761–2766. Cognitive Science Society.
, , and (2008). A computational model of the visual oddity task. In Proceedings of the 30th Annual Conference of the Cognitive Science Society, volume 25, page 29. Cognitive Science Society.
(1985). Abortion and the civil rights of machines. In Morality and universality, pages 139–156. Springer.
(2008). Collective problem solving: Are the many smarter than the few. Durhan Anthropology Journal, 15(1):23–58.Google Scholar
(1996). Dysgenics: Genetic deterioration in modern populations. Praeger.
(2001). Eugenics: A reassessment. Greenwood.
, , and (2012). Interactive language learning by robots: The transition from babbling to word forms. PloS ONE, 7(6):e38236.Google Scholar
, , and (2013). An introduction to evolutionary developmental psychology. Evolutionary Psychology, 12(2):264–272.Google Scholar
and (2014). Towards UCI+: A mindful repository design. Information Sciences, 261:237–262.Google Scholar
, , , , and (2009). Everyone's a critic: Memory models and uses for an artificial Turing judge. In the 2nd Conference on Artificial General Intelligence, pages 132–137. Atlantis Press.
and (2011). IQ and human intelligence. Oxford University Press.
and (2004). Transfer of experience between reinforcement learning environments with progressive difficulty. Artificial Intelligence Review, 21(3–4):375–398.Google Scholar
, , and (2009). Performance evaluation and benchmarking of intelligent systems. Springer.
, , , and (2012). Dolphin whistles: A functional misnomer revealed by heliox breathing. Biology Letters, 8(2):211–213.Google Scholar
(1999). Text compression as a test for artificial intelligence. In Proceedings of the National Conference on Artificial Intelligence, pages 970–970. AAAI.
(1958). Potential intelligence: A learning theory approach to description and clinical implication. Journal of General Psychology, 59(1):59–71.Google Scholar
and (2013). A survey of techniques for characterising fitness landscapes and some possible ways forward. Information Sciences, 241:148–163.Google Scholar
W. and , editors(2015). Handbook of collective intelligence. MIT Press.
, , , , , and (2009). Spatial competences inWilliams syndrome: Aradial armmaze study. International Journal of Developmental Neuroscience, 27(3):205–213.Google Scholar
(1996). Psychological evaluation of children who are deaf-blind: An overview with recommendations for practice. National Consortium on Deaf-Blindness.
and (2007). The termination competition. In Term rewriting and applications, pages 303–313. Springer.
, , , , and (2014). Give a hard problem to a diverse team: Exploring large action spaces. Proceedings of 28th AAAI. AAAI.
, , and (2015). Beyond the Turing test. AAAI workshop, http://www.math.unipd.it/∼frossi/BeyondTuring2015/.
, , , eds.(2016). Beyond the Turing test (special issue). AI Magazine, 37(1):3–101.
, ,, , and (2014). Psycho-informatics: Big data shaping modern psychometrics. MedicalHypotheses, 82(4):405–411.Google Scholar
, , and (1983). The complexity continuum in the radex and hierarchical models of intelligence. Intelligence, 7(2):107–127.Google Scholar
, , and (2015). A computational analysis of general intelligence tests for evaluating cognitive development. Unpublished manuscript.
, , , and (2015). Knowledge acquisition with forgetting: An incremental and developmental setting. Adaptive Behavior, 23(5):283–299.Google Scholar
and (2003). The Turing ratio: A framework for open-ended task metrics. Journal of Evolution and Technology, 13(2).Google Scholar
, , and (2002). The Turing ratio: Metrics for open-ended tasks. In GECCO, Proceedings of the Genetic and Evolutionary Computation Conference, pages 973–980. Morgan Kaufmann.
and (1980). Autopoiesis and cognition: The realization of the living. Kluwer.
and (2010). Selective attention, working memory, and animal intelligence. Neuroscience and Biobehavioral Reviews, 34(1):23–30.Google Scholar
(2013). The engine of complexity: Evolution as computation. Columbia University Press.
(1982). The growth of biological thought:Diversity, evolution, and inheritance. Harvard University Press.
(1979). Ascribing mental qualities to machines. In , editor, Philosophical perspectives in artificial intelligence, pages 161–195. Humanities Press.
(1983). Artificial intelligence needs more emphasis on basic research: President's quarterly message. AI Magazine, 4(4):5.Google Scholar
(1987). Generality in artificial intelligence. Communications of the ACM, 30(12):1030–1035.Google Scholar
(2007). What is artificial intelligence? Technical report, Stanford University. http://www-formal.stanford.edu/jmc/whatisai.html.
(1973). Testing for competence rather than for “intelligence”. American Psychologist, 28(1):1.Google Scholar
(2004). Machines who think. A K Peters/CRC Press.
and (2010). Neo inventories professional manual. Psychological Assessment Resources.
(1997). How intelligent is Deep Blue? New York Times, May 14.
(2010). Don't improve the Turing test, abandon it. In , , , , editors, AISB 2010 Symposium “Towards a Comprehensive Intelligence Test (TCIT): Reconsidering the Turing Test for the 21st Century”, pages 37–41. Society for the Study of Artificial Intelligence and the Simulation of Behaviour.
, , , , , , , , , , and (2012). Genetic programming needs better benchmarks. In International Conference on Genetic and Evolutionary Computation, pages 791–798. ACM.
(1984). Groups: Interaction and performance. Prentice Hall.
, ,, and (2001). The use of behavioral test batteries: Effects of training history. Physiology and Behavior, 73(5):705–717.Google Scholar
(2014). The no free lunch theorem and hypothesis of instinctive animal behavior. Artificial Intelligence Research, 3(4):43.Google Scholar
(2010). The extended mind. MIT Press.
W.(2001). Assessment of children's social skills: Recent developments, best practices, and new directions. Exceptionality, 9(1–2):3–18.Google Scholar
(1998). Phase transition in the number partitioning problem. Physical Review Letters, 81(20):4281.Google Scholar
, , and (2001). PerMIS 2001, white paper. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2001 PerMIS Workshop, pages 3–15. NIST Special Publication 982. NIST.
(2000a). Appendix A. The preliminary discussions. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 563–642. NIST Special Publication 970. NIST.
(2000b). Permis 2000 white paper: Measuring performance and intelligence of systems with autonomy. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 1–34. NIST Special Publication 970. NIST.
, , , and (2003a). Performance measures for intelligent systems: Measures of technology readiness. Technical report, DTIC Document.
, , , and (2003b). Permis 2003 white paper: Performance measures for intelligent systems – measures of technology readiness. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2003 PerMIS Workshop. NIST Special Publication 1014. NIST.
and (2001). Evaluating the performance of e-coli with genetic learning from simulated testing. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2001 PerMIS Workshop. NIST Special Publication 982. NIST.
and (2008). The rat's life benchmark: Competing cognitive robots. In and , editors, Proceedings of the 8th Workshop on Performance Metrics for Intelligent Systems, pages 43–49. ACM.
(2000). Normal science, pathological science and psychometrics. Theory and Psychology, 10(5):639–667.Google Scholar
and (2016). The power of crowds. Science, 351(6268):32–33.
(2010). Social savvy boosts the collective intelligence of groups. Science, 330(6000):22–22.Google Scholar
(1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63(2):81.Google Scholar
(1995). Wordnet: A lexical database for English. Communications of the ACM, 38(11):39–41.Google Scholar
, editor(1968). Semantic information processing. MIT Press.
(1988). Society of mind. Simon and Schuster.
, , , , , , , , , , , , , , , , , , and (2015). Human-level control through deep reinforcement learning. Nature, 518(26 February):529–533.Google Scholar
(1931). Conference on examinations. Teachers College, Columbia University.
(2003). The Turing test: The elusive standard of artificial intelligence, volume 30. Springer Science and Business Media.
(2011). The nature of computation. Oxford University Press.
(1988). Mind children: The future of robot and human intelligence. Harvard University Press.
(1903). An introduction to comparative psychology. W. Scott.
, , and (2016). Planning, executing, and evaluating the Winograd schema challenge. AI Magazine, 37(1):50–54.Google Scholar
and (2015). The Winograd schema challenge: Evaluating progress in commonsense reasoning. In The Twenty-Ninth AAAI Conference on Artificial Intelligence, pages 4024–4026. AAAI.
(1967). The naked ape: A zoologist's study of the human animal. Jonathan Cape.
, , , and (1925). George Washington University social intelligence test. Cen.
(1987). Daydreaming and computation. Technical report, TR, CSD- 870017. PhD dissertation, University of California, Los Angeles.
(2008). Is the Turing Test still relevant? A plan for developing the cognitive decathlon to test intelligent embodied behavior. In 19th Midwest Artificial Intelligence and Cognitive Science Conference.
(2010). A partial implementation of the BICA cognitive decathlon using the psychology experiment building language (PEBL). International Journal of Machine Consciousness, 2(02):273–288.Google Scholar
, , , and (2007). The BICA cognitive decathlon: A test suite for biologically-inspired cognitive agents. In Proceedings of Behavior Representation in Modeling and Simulation Conference, Norfolk.
and (2014). The Psychology Experiment Building Language (PEBL) and PEBL test battery. Journal of Neuroscience Methods, 222:250–259.Google Scholar
(2006). A critique of emotional intelligence: What are the problems and how can they be fixed?
Psychology Press.
, , and (2013). Spearman's law of diminishing returns: A statistical artifact. Intelligence, 41(5):439–451.Google Scholar
, , and (2011). The art of software testing. JohnWiley.
, , and (2000). Intelligence:Maze-solving by an amoeboid organism. Nature, 407(6803):470–470.Google Scholar
(1996). Verification of a human in the loop or identification via the Turing test. http://www.wisdom.weizmann.ac.il/∼naor/PAPERS/human_abs.html.
, , , , , , , , and (2007). Relationships between IQ and regional cortical gray matter thickness in healthy adults. Cerebral Cortex, 17(9):2163–2171.Google Scholar
,, , , and (1995). Can computer personalities be human personalities. International Journal of Human-Computer Studies, 43(2):223–239.Google Scholar
and (2006). P-completeness of cellular automaton rule 110. In Automata, Languages and Programming, pages 132–143. Springer.
and (2007). Imitation and social learning in robots, humans and animals: Behavioural, social and communicative dimensions. Cambridge University Press.
(2006). The evolution of personality variation in humans and other animals. American Psychologist, 61(6):622.Google Scholar
, , and (2009). Variations of the Turing test in the age of Internet and virtual reality. In KI 2009: Advances in Artificial Intelligence, pages 355–362. Springer.
, , , , , et al.(1984). Battelle developmental inventory. DLM Teaching Resources.
and (2008). Test of Language Development: Primary (TOLD-P: 4). PRO-ED.
(1973). You can't play 20 questions with nature and win: Projective comments on the papers of this symposium. In , editor, Visual information processing, pages 283–308. Academic Press.
(1990). Unified theories of cognition. Harvard University Press.
, , and (1959). Report on a general problem-solving program. In International Conference on Information Processing, pages 256–264. UNESCO.
and (1961). GPS, a program that simulates human thought. Technical report, DTIC Document.
and (1976). Computer science as empirical inquiry: Symbols and search. Communications of the ACM, 19(3):113–126.Google Scholar
, , et al.(2000). Algorithms for inverse reinforcement learning. In International Conference on Machine Learning, pages 663–670. Morgan Kaufman.
(1980). Principles of artificial intelligence. Morgan Kaufmann.
(2009). The quest for artificial intelligence. Cambridge University Press.
, , , , , , and (2012). Intelligence: New findings and theoretical developments. American Psychologist, 67(2):130.Google Scholar
, , , , , , , , , , , , and (2014).Autonomous acquisition of natural language. InA. P. dos Reis P. Kommers, and P. Isaías (Eds.), Proceedings of the IADIS International Conference on Intelligent Systems & Agents 2014 (ISA-14), pages 58–66.
and (2006). Book review: Marcus Hutter, universal artificial intelligence. Artificial Intelligence, 170:1222–1226.Google Scholar
, , , and (2013). Verbal IQ of a four-year-old achieved by an AI system. In COMMONSENSE 2013, 11th International Symposium on Logical Formalizations of Commonsense Reasoning, Ayia Napa, Cyprus, page 6. Commonsense Reading.
, , , and (2015). Measuring an artificial intelligence system's performance on a verbal IQ test for young children. CoRR arXiv preprint:1509.03390.
and (1976). Remembrance of places passed: Spatial memory in rats. Journal of Experimental Psychology: Animal Behavior Processes, 2(2):97.Google Scholar
(2012). Rational artificial intelligence for the greater good. In , , , and , editors, Singularity hypotheses, pages 161–179. Springer.
and (2011). The Turing test. In , editor, Stanford encyclopedia of philosophy. Stanford University. http://plato.stanford.edu/entries/turing-test/.
(2013). Asymptotic non-learnability of universal agents with computable horizon functions. Theoretical Computer Science, 473:149–156.Google Scholar
(2014). Universal knowledge-seeking agents. Theoretical Computer Science, 519:127–139.Google Scholar
, , and (2013). Universal knowledge-seeking agents for stochastic environments. In Algorithmic learning theory, pages 158–172. Springer.
and (2011). Self-modification and mortality in artificial agents. In , , and , editors, 4th Conference on Artificial General Intelligence, pages 1–10. Lecture Notes in Artificial Intelligence, volume 6830. Springer.
, , and (2013). Predicting user personality by mining social interactions in facebook. Journal of Computer and System Sciences, 80:57–71.Google Scholar
, Jr.(2016). Why we need a physically embodied Turing test and what it might look like. AI Magazine, 37(1):55–62.Google Scholar
(1949). Nineteen Eighty-Four. Secker and Warburg.
, , and (1965). Measurement of social intelligence. ERIC, University of South California.
(2015). Language development: An introduction, 9th edition. Pearson.
(2008). The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton University Press.
and (2005). Cooperative multi-agent learning: The state of the art. Autonomous Agents and Multi-Agent Systems, 11(3):387–434.Google Scholar
, , , , , , , and P.(2015). Automatic personality assessment through social media language. Journal of Personality and Social Psychology, 108(6):934.Google Scholar
, , and (2001).Measuring the machine intelligence quotient (MIQ) of human-machine cooperative systems. IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems and Humans, 31(2):89–96.Google Scholar
and (2012). Origins of intelligence: The evolution of cognitive development in monkeys, apes, and humans. Johns Hopkins University Press.
(2004). Hedonistic imperative. http://www.hedweb.com/.
, , and (2008). Darwin's mistake: Explaining the discontinuity between human and nonhuman minds. Behavioral and Brain Sciences, 31(2):109–130.Google Scholar
, , , and (2012). Putting the elephant back in the herd: Elephant relative quantity judgmentsmatch those of other species. Animal Cognition, 15(5):955–961.Google Scholar
, , , , , , , , and (2015). The 2014 general video game playing competition. IEEE Transactions on Computational Intelligence and AI in Games.
(1970). Personality: Theory, assessment, and research.
John Wiley.
PETRL(2015). People for the ethical treatment of reinforcement learners. http://petrl.org/.
(1936). La naissance de l'intelligence chez l'enfant. Delachaux et Niestlé. (English translation 1952: “The origins of intelligence in children”).
(1964). Cognitive development in children. Journal of Research in Science Teaching, 2(3):176–186.Google Scholar
(1995). The language instinct: The new science of language and mind, volume 7529. Penguin.
(2003). The blank slate: The modern denial of human nature. Penguin.
(2009). Language learnability and language development, with new commentary by the author. Harvard University Press.
(1921). Intelligence and its measurement: A symposium. Journal of Educational Psychology, 12(3):139.Google Scholar
(2017). Is the universe a hologram? And other conversations with leading scientists. MIT Press.
(2001). The genetics of g in human and mouse. Nature Reviews Neuroscience, 2(2):136–141.Google Scholar
and (2005). Nature and nurture: Genetic and environmental influences on behavior. Annals of the American Academy of Political and Social Science, 600(1):86–98.Google Scholar
and (2015). Genetics and intelligence differences: Five special findings. Molecular Psychiatry, 20:98–108.Google Scholar
, , , and (2013). Behavioral Genetics. Palgrave Macmillan.
and (2005). Asymptotics of discrete MDL for online prediction. IEEE Transactions on Information Theory, 51(11):3780–3795.Google Scholar
and (2006). MDL convergence speed for Bernoulli sequences. Statistics and Computing, 16(2):161–175.Google Scholar
, , Colbry, , , , , and (2003). Autominder: An intelligent cognitive orthotic system for people with memory impairment. Robotics and Autonomous Systems, 44(3):273–282.Google Scholar
, , , , , , , and (2013). Overview of the 5th international competition on plagiarism detection. In CLEF 2013 Evaluation Labs and Workshop Working Notes Papers, 23–26 September, Valencia, Spain.
and (2005). Technologies for working intelligence. In and , editors, Intelligence and technology: The impact of tools on the nature and development of human abilities, pages 183–208. Routledge.
(1991). AI, anthropocentrism, and the evolution of ‘intelligence’. Minds and Machines, 1(3):259–277.
Princeton University(2010). About Wordnet. http://wordnet.princeton.edu/.
(2011). Anthropomorphism and AI: Turing's much misunderstood imitation game. Artificial Intelligence, 175(5):950–957.Google Scholar
and (2006). Animal pattern-learning experiments: Some mathematical background. Radcliffe Institute for Advanced Study/Harvard University.
and (2002). Empirical assessment of stimulus poverty arguments. The Linguistic Review, 18(1–2):9–50.Google Scholar
and (2009). For universals (but not finite-state learning) visit the zoo. Behavioral and Brain Sciences, 32(5):466–467.Google Scholar
, , , , and (2016). Optomechanical quantum correlation thermometry. Bulletin of the American Physical Society. APS March Meeting 2016, abstract #P52.011. APS.
, , , and (2011). Our Twitter profiles, our selves: Predicting personality with Twitter. In Third International Conference on Social Computing (SOCIALCOM), pages 180–185. IEEE.
and (2011). Human computation: A survey and taxonomy of a growing field. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1403–1412. ACM.
(2012). Borges and memory: Encounters with the human brain. MIT Press.
and (2012). Solving Raven's IQ-tests: An AI and cognitive modeling approach. In ECAI, pages 666–671. IOS Press.
and (2014).Analyzing Raven's intelligence test: Cognitive model, demand, and complexity. In and , editors, Computational approaches to analogical reasoning: Current trends, pages 351–370. Studies in Computational Intelligence, volume 548. Springer.
(2011). Artificial intelligence – man or machine. International Journal of Information Technology, 4(1):173–176.Google Scholar
(1960). Probabilistic models for some intelligence and attainnment tests. Danmarks paedagogiske Institut.
, , and (1992). Manual for Raven's Progressive Matrices and Vocabulary Scale. Psychological Corporation.
, , and (2011). The evolution of primate general and cultural intelligence. Philosophical Transactions of the Royal Society, Series B, 366(1567):1017–1027.Google Scholar
(1987). The case for animal rights. Springer.
and (2013). The general factor of personality: A general critique. Journal of Research in Personality, 47(5):493–504.Google Scholar
(2007). Animal intelligence: From individual to social cognition. Cambridge University Press.
and (2003). In the shadow of the binary tree: Of ants and bits. In Proceedings of the 2nd Intl Workshop of the Mathematics and Algorithms of Social Insects, pages 139–145. Georgian Institute of Technology.
and (1933). A note on the use of bi-serial r in test research. Journal of General Psychology, 8(2):463–465.Google Scholar
(1986).Assessment of basic social skills. Journal of Personality and Social Psychology, 51(3):649.Google Scholar
and (2011). Delusion, survival, and intelligent agents. In , , and , editors, 4th Conference on Artificial General Intelligence, pages 11–20. Lecture Notes in Artificial Intelligence, volume 6830. Springer.
, ,, and (1997). Personality-driven social behaviors in believable agents. In Proceedings of the AAAI Fall Symposium on Socially Intelligent Agents, pages 109–114. AAAI.
(2001). Task complexity, task difficulty, and task production: Exploring interactions in a componential framework. Applied Linguistics, 22(1):27–57.Google Scholar
(2010). Accelerating progress in artificial general intelligence: Choosing a benchmark for natural world interaction. Journal of Artificial General Intelligence, 2(1):1–28.Google Scholar
(2003). Stanford-Binet intelligence scales. Riverside. (1885). Mind in men and animals. The North American Review, pages 251–257.
and (2001). A review and evaluation of research on the deaf-blind from perceptual, communicative, social and rehabilitative perspectives. Scandinavian Audiology, 30(2):67–77.Google Scholar
and (2013). Evolution of nervous systems and brains. In and , editors, Neurosciences – from molecule to behavior: A university textbook, pages 19–45. Springer.
and (2014). Measuring cognition will be difficult but worth it: A response to comments on Rowe and Healy. Behavioral Ecology, 24:1298.Google Scholar
(2014). Language learning by a chimpanzee: The Lana project. Academic Press.
, , (1985). Learning internal representations by error propagation. Technical report, DTIC Document.
and (1994). On-line Q-learning using connectionist systems. Cambridge University Engineering Department, TR 166.
(1936). Intelligence test scores and school marks in 1928 and 1933. School and Society, 43:301–304.Google Scholar
(2015). The long-term future of (artificial) intelligence. AAAI 2015 invited talk.
, , , , , , , , , , et al.(2015). Research priorities for robust and beneficial artificial intelligence: an open letter. Future of Life Institute (FLI). http://arxiv.org/abs/1602.03506.
and (2009). Artificial intelligence: A modern approach, 3rd edition. Prentice Hall.
and (2009). Modern psychometrics: The science of psychological assessment. Routledge.
and (2009). The use of ideas of information theory for studying “language” and intelligence in ants. Entropy, 11(4):836–853.Google Scholar
and (2011). Instrumenting the crowd: Using implicit behavioral measures to predict task performance. In Proceedings of the 24th annual ACM Symposium on User Interface Software and Technology, pages 13–22. ACM.
and (1995). International handbook of personality and intelligence. Springer Science and Business Media.
(2012). Collective intelligence in humans: A literature review. CoRR arXiv preprint:1204.3401.
(1976). “Neural capacity” inMimosa pudica: A review. Behavioral Biology, 17(4):435–452.Google Scholar
(2000). Minimal representation size metrics for intelligent robotic systems. In
, editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMISWorkshop, pages 127–134. NIST Special Publication 970. NIST.
and (2003). A computer program capable of passing IQ tests. In 4th International Conference on Cognitive Science (ICCS-03), Sydney, pages 570–575. International Association for Cognitive Science.
and (1994). Kanzi: The ape at the brink of the human mind. John Wiley.
and (2015). Use of open-source software for adaptive measurement: Concerto as an R-based computer adaptive development and delivery platform. British Journal of Mathematical and Statistical Psychology, 68(3):478–496, available at http://concertoplatform.com/.Google Scholar
(2010). Primary mental abilities. In and , editors, Corsini encyclopedia of psychology, pages 1286–1288. John Wiley.
, , and (2004). The Seattle longitudinal study: Relationship between personality and cognition. Aging Neuropsychology and Cognition, 11(2–3):304–324.Google Scholar
(2014). An extensible description language for video games. IEEE Transactions on Computational Intelligence and AI in Games, 6(4):325–331.Google Scholar
(2013). Intelligence tests for robots: Solving perceptual reasoning tasks with a humanoid robot. Master's thesis, Iowa State University.
, , and (2012).Which object comes next? Grounded order completion by a humanoid robot. Cybernetics and Information Technologies, 12(3):5–16.Google Scholar
and (2012). The object pairing and matching task: Toward Montessori tests for robots. In , , , and , editors, Proceedings of Humanoids 2012 Workshop on Developmental Robotics: Can developmental robotics yield human-like cognitive abilities?, pages 7–13. IEEE.
(1979). A method of assessing bias in test items. Journal of Educational Measurement, 16(3):143–152.Google Scholar
, , and (2011). Performance evaluation of intelligent systems at the NIST. Technical report, DTIC Document.
(2007). Gödel machines: Fully self-referential optimal universal selfimprovers. In and , editors Artificial general intelligence, pages 199–226. Springer.
, , and (2012). Old world monkeys compare to apes in the primate cognition test battery. PloS ONE, 7(4):e32024.Google Scholar
(1999). An empirical test of a process model for letter series completion problems. In and , editors, Knowledge spaces: Theories, empirical research, applications, pages 133–154. Lawrence Erlbaum Associates.
(1965). An essential unpredictability in human behavior. In and , editors, Scientific psychology: Principles and approaches, pages 411–425. Basic Books.
and (2006). Compression and machine learning: A new perspective on feature space vectors. In Data Compression Conference, pages 332–341. IEEE.
and (1981). The Clever Hans phenomenon: Communication with horses, whales, apes, and people.
New York Academy of Sciences.
, , , and (2001). Learning differences between feral pigeons and zenaida doves: The role of neophobia and human proximity. Ethology, 107(4):281–293.Google Scholar
(2012). Human-enculturated apes: Towards a new synthesis of philosophy and comparative psychology. In and , editors, Crossing boundaries: Investigating human-animal relationships, chapter 7, pages 139–159. BRILL.
,, and (1996). CELF 3, Clinical Evaluation of Language Fundamentals: Observational rating scales. Psychological Corporation.
and (2007). Towards a theory of AI completeness. In AAAI Spring Symposium: Logical Formalizations of Commonsense Reasoning, pages 150–155. Commonsense Reasoning.
and (2010). Generalized task markets for human and machine computation. In National Conference on Artificial Intelligence, pages 986–993. AAAI.
(2015). The technological singularity. MIT Press.
(1948). A mathematical theory of communication. Bell System Technical Journal, 27:379–423, 623–656.Google Scholar
(1992). Encyclopedia of artificial intelligence, 2nd edition. John Wiley.
, , , and (2015). An approach to solve Winograd schema challenge using automatically extracted commonsense knowledge. In 2015 AAAI Spring Symposium Series, pages 141–144. AAAI.
(2009). The evolution of comparative cognition: Is the snark still a boojum. Behavioural Processes, 80(3):210–217.Google Scholar
(2010a). Clever animals and killjoy explanations in comparative psychology. Trends in Cognitive Sciences, 14(11):477–481.Google Scholar
(2010b). Cognition, evolution, and behavior, 2nd edition. Oxford University Press.
(2013). Fundamentals of comparative cognition. Oxford University Press.
(2004). The Turing test: Verbal behavior as the hallmark of intelligence. MIT Press.
(1940). A self-administering scale for measuring intellectual impairment and deterioration. Journal of Psychology, 9(2):371–377.Google Scholar
(2009).On the use, themisuse, and the very limited usefulness of Cronbach's alpha. Psychometrika, 74(1):107–120.Google Scholar
(2012). Future of psychometrics: Ask what psychometrics can do for psychology. Psychometrika, 77(1):4–20.Google Scholar
(2000). Survivability and competence as measures of intelligent systems. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 162–163. NIST Special Publication 970. NIST.
(1978). On the forms of mental representation. Perception and Cognition: Issues in the Foundations of Psychology, 9:3–18.Google Scholar
(1980). Cognitive science: The newest science of the artificial. Cognitive Science, 4(1):33–46.Google Scholar
(1982). Models of bounded rationality: Empirically grounded economic reason, volume 3. MIT Press.
and (1963). Human acquisition of concepts for sequential patterns. Psychological Review, 70(6):534.Google Scholar
, , and (1991). SCSoar: Pattern induction in series completion problem solving. In European SoarWorkshop, page 17. Cambridge University Press.
and (2008). Refining the cognitive decathlon. In
, editors, Proceedings of the 8thWorkshop on PerformanceMetrics for Intelligent Systems, pages 124–131. NIST.
and (2010). The odd one out task: Toward an intelligence test for robots. In 2010 IEEE 9th International Conference on Development and Learning (ICDL), pages 126–131. IEEE.
(1995). Animal liberation. Random House.
and (2006). Preschoolers out of adults: Discriminative learning with a cognitive load. Quarterly Journal of Experimental Psychology, 59(8):1357–1377.Google Scholar
(1938). The behavior of organisms: An experimental analysis.
Appleton- Century.
(1978). The computer revolution in philosophy: Philosophy, science and models of mind, volume 3. Harvester Press Brighton. Freely available version with updates, 2009, http://www.cs.bham.ac.uk/research/projects/cogaff/crp/crp.pdf.
(1984). The structure and space of possible minds. In , editor, The mind and the machine: Philosophical aspects of artificial intelligence, pages 35–42. Ellis Horwood.
(2006). Why Asimov's three laws of robotics are unethical. http://www.cs.bham.ac.uk/research/projects/cogaff/misc/asimov-three-laws.html.
(2009). Some requirements for human-like robots: Why the recent overemphasis on embodiment has held up progress. In Creating brain-like intelligence, pages 248–277. Springer.
(2014a). Judging chatbots at Turing test. http://www.cs.bham.ac.uk/research/projects/cogaff/misc/turing-test-2014.html.
(2014b). Judging chatbots without opening them: Limitations of ‘black-box’ tests. http://www.cs.bham.ac.uk/research/projects/cogaff/misc/black-box-tests.html.
(2016). Construction kits for biological evolution. In and , editors, The incomputable. Springer. To appear.
(2001). Animal cognition and the rat olfactory system. Trends in Cognitive Sciences, 5(5):216–222.Google Scholar
(2010). What is a person? Rethinking humanity, social life, and the moral good from the person up. University of Chicago Press.
and (2003). Animal signals. Oxford University Press.
(2009). The trouble with intrinsic value: An ethical primer for astrobiology. In Bertka, C.M., editor, Exploring the origin, extent, and future of life, pages 261–280. Cambridge University Press.
(2014).Manifest complexity: A foundational ethic for astrobiology?
Space Policy, 30(4):209–214.Google Scholar
(2002). Rating systems for gameplayers, and learning. Technical Report, NEC.
(2006). Mathematical definition of “intelligence” (and consequences). Unpublished report.
, , and (1984). The topography of ability and learning correlations. Advances in the Psychology of Human Intelligence, 2:47–103.Google Scholar
(2009). UCI++: Improved support for algorithm selection using datasetoids. In Advances in knowledge discovery and data mining, pages 499–506. Springer.
, , , and (2015). Corrigibility. In AAAI-15 Workshop on AI and Ethics, pages 74–82. AAAI.
(2005). Longitude: The true story of a lone genius who solved the greatest scientific problem of his time. Macmillan.
, , , and (2012). Giving robots a flexible persona: The five factor model of artificial personality in action. In 12th International Conference on Control, Automation and Systems (ICCAS), pages 133–139. IEEE.
, , , and (2014). Calculating Kolmogorov complexity from the output frequency distributions of small Turing machines. PloS ONE, 9(5):e96223.Google Scholar
(2010). (1926–2009). Algorithms, 3(3):255–259.
(1960). A preliminary report on a general theory of inductive inference. Report V-131, Zator Co.
(1962). Training sequences for mechanized induction. In , , and , editors, Self-organizing systems, pages 425–434. Spartan Books.
(1964a). A formal theory of inductive inference. Part I. Information and Control, 7(1):1–22.Google Scholar
(1964b). A formal theory of inductive inference. Part II. Information and Control, 7(2):224–254.Google Scholar
(1978). Complexity-based induction systems: Comparisons and convergence theorems. IEEE Transactions on Information Theory, 24(4):422–432.Google Scholar
(1984a). Optimum sequential search. Oxbridge Research. http://raysolomonoff.com/publications/optseq.pdf.
(1984b). Perfect training sequences and the costs of corruption – a progress report on induction inference research. Oxbridge Research. http://raysolomonoff.com/publications/perfecttraining.pdf.
(1985). The time scale of artificial intelligence: Reflections on social effects. Human Systems Management, 5:149–153.Google Scholar
(1989). A system for incremental learning based on algorithmic probability. In Proceedings of the Sixth Israeli Conference on Artificial Intelligence, Computer Vision and Pattern Recognition, pages 515–527. Information Processing Association of Israel.
(1996). Does algorithmic probability solve the problem of induction. In , , and , editors, Proceedings of the Information, Statistics and Induction in Science (ISIS) Conference, Melbourne, Australia, pages 7–8. World Scientific.
(1997). The discovery of algorithmic probability. Journal of Computer and System Sciences, 55(1):73–88.Google Scholar
(2002). Progress in incremental machine learning. In NIPS Workshop on Universal Learning Algorithms and Optimal Search, Whistler, BC.
and (2007). Complexity of self-assembled shapes. SIAM Journal on Computing, 36(6):1544–1569.Google Scholar
, , and M.(2011). Google effects on memory: Cognitive consequences of having information at our fingertips. Science, 333(6043):776–778.Google Scholar
(2012). Can machines be people? reflections on the Turing triage test. In , , and , editors, Robot ethics: The ethical and social implications of robotics, pages 301–315. MIT Press.
(1904).General intelligence, objectively determined and measured.
American Journal of Psychology, 15(2):201–292.Google Scholar
(1925). Some issues in the theory of “g” (including the law of diminishing returns). Nature, 116:436–439.Google Scholar
(1927). The abilities of man: Their nature and measurement. Macmillan.
(1986). The raising of intelligence: A selected history of attempts to raise retarded intelligence. Routledge.
, , and (2010). Knowledge space theory, formal concept analysis, and computerized psychological assessment. Behavior Research Methods, 42(1):342–350.Google Scholar
, , , and (2006). Adaptive game AI with dynamic scripting. Machine Learning, 63(3):217–248.Google Scholar
, , and (2003). Improving opponent intelligence through offline evolutionary learning. International Journal of Intelligent Games and Simulation, 2(1):20–27.Google Scholar
, , and (2004). Difficulty scaling of game AI. In Proceedings of the 5th International Conference on Intelligent Games and Simulation (GAME-ON 2004), pages 33–37. The European Multidisciplinary Society for Modelling and Simulation Technology.
(2002). Importance sampling: Applications in communications and detection. Springer.
, , , , , and (2012). Friends don't lie: Inferring personality traits from social network structure. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pages 321–330. ACM.
(2000). Complexity, metacognition, and fluid intelligence. Intelligence, 28(2):121–143.Google Scholar
, van , and (2006). The Tenjinno machine translation competition. In Grammatical inference: Algorithms and applications, pages 214–226. Springer.
(2011). Design patterns in fluid construction grammar, volume 11. John Benjamins.
, , , , and (2012). Emergent action language on real robots. In Language grounding in robots, pages 255–276. Springer.
(1966).Models for inferring relationships between group size and potential group productivity. Behavioral Science, 11(4):273–283.Google Scholar
(1974). The evolution of intelligence. Barnes and Noble.
(1912). Die psychologischen Methoden der Intelligenzprüfung und deren Anwendung an Schulkindern. Barth.
(1977). Intelligence, information processing, and analogical reasoning: The componential analysis of human abilities.
Lawrence Erlbaum Associates.
(1985). Beyond IQ: A triarchic theory of human intelligence. Cambridge University Press.
(1997). A triarchic view of giftedness: Theory and practice. Handbook of Gifted Education, 2:43–53.Google Scholar
(1999). Intelligence as developing expertise. Contemporary Educational Psychology, 24(4):359–375.Google Scholar
, editor(2000). Handbook of intelligence. Cambridge University Press.
, , , and (1981). People's conceptions of intelligence. Journal of Personality and Social Psychology, 41(1):37.Google Scholar
and , (1983). Unities in inductive reasoning. Journal of Experimental Psychology: General, 112(1):80.Google Scholar
, L., , , , , ,, , ,, , and (2015). Citizen science as a new tool in dog cognition research. PloS ONE, 10(9):e0135176.Google Scholar
, , , , (2010). Ad hoc autonomous agent teams: Collaboration without pre-coordination. In Proceedings of the Twenty-Fourth AAAI Conference on Artificial Intelligence, pages 1504–1509. AAAI.
(1998). Scientist on the set: An interview with Marvin Minsky. In HAL's legacy: 2001's computer as dream and reality, pages 15–32. MIT Press.
, J., , , , , , and , (1997). Absence of within-colony kin discrimination in behavioural interactions of swarm-founding wasps. Proceedings of the Royal Society of London, Series B, 264(1388):1565.Google Scholar
(2012). Benchmarks for grid-based pathfinding. Transactions on Computational Intelligence and AI in Games, 4(2):144–148.Google Scholar
(2009). The TPTP Problem Library and associated infrastructure: The FOF and CNF Parts, v3.5.0. Journal of Automated Reasoning, 43(4):337–362.Google Scholar
and (2014). Deep brain stimulation for enhancement of learning and memory. Neuroimage, 85:996–1002.Google Scholar
and G.(1998). Reinforcement learning: An introduction. MIT Press.
and (2002). Personality traits in the domestic dog (Canis familiaris). Applied Animal Behaviour Science, 79(2):133–155.
, D., and , (2012). Real-time feedback-controlled robotic fish for behavioral experiments with fish schools. Proceedings of the IEEE, 100(1):150–163.Google Scholar
(1986). Giftedness: A psychosocial approach. In and , editors, Conceptions of giftedness, pages 21–52. Cambridge University Press.
, , and (2006). Quantifying patterns of agent–environment interaction. Robotics and Autonomous Systems, 54(2):150–158.Google Scholar
(1943). Chinese influence on the Western examination system: I. Introduction. Harvard Journal of Asiatic Studies, 7(4):267–312.Google Scholar
(1922). The great conspiracy or the impulse imperious of intelligence testers, psychoanalyzed and exposed by Mr. Lippmann. New Republic, 33(27 December):116–120.Google Scholar
(1987). Nim: A chimpanzee who learned sign language. Columbia University Press.
(1994). TD-Gammon, a self-teaching backgammon program, achieves master-level play. Neural Computation, 6(2):215–219.Google Scholar
(1978). The best explanation: Criteria for theory choice. Journal of Philosophy, 75(2):76–92.Google Scholar
, , and L.(2010). Recognizing group cognition. Cognitive Systems Research, 11(4):378–395.Google Scholar
(1996). Investigating cognitive abilities in animals: Unrealized potential. Cognitive Brain Research, 3(3):157–166.Google Scholar
, , , , , , , , , , et al.(2001). Genetic influences on brain structure. Nature Neuroscience, 4(12):1253–1258.Google Scholar
(2012). Sampling, 3rd edition. John Wiley.
, , , and (2015). Towards flexible task environments for comprehensive evaluation of artificial intelligent systems and automatic learners. In , , and , editors, International Conference on Artificial General Intelligence, pages 187–196. Springer.
(1911). Animal intelligence: Experimental studies. Macmillan.
, , , and (1927). The measurement of intelligence. Teachers College Bureau of Publications, Columbia University.
(1935). Organization of behavior in the albino rat. Genetic Psychology Monographs. Heldref.
(1936). Factor analysis of social and abstract intelligence. Journal of Educational Psychology, 27(3):231.Google Scholar
, , and R.(2014). Toward wild psychometrics: Linking individual cognitive differences to fitness. Behavioral Ecology, aru095.
and (2012). Individual variation in cognitive performance: Developmental and evolutionary perspectives. Philosophical Transactions of the Royal Society, Series B, 367(1603):2773–2783.Google Scholar
and R.(1959). Predicting potential intelligence. Journal of Clinical Psychology, 15(3):286–288.Google Scholar
(1938). Primary mental abilities. Psychometric Monographs.
and G.(1941). Factorial studies of intelligence. Psychometrika Monograph Supplements. University of Chicago Press.
and G.(1947). American Council on Education for college freshmen: Manual of instructions. Cooperative Test Division, Educational Testing Service.
(1963). On aims and methods of ethology. Zeitschrift für Tierpsychologie, 20(4):410–433.Google Scholar
, N., , and (2012). Assessing believability. In , editor, Believable bots, pages 215–230. Springer.
(2006). Acquiring linguistic constructions, volume two. In and , editors, Handbook of child psychology, 255–298. John Wiley.
and (1997). Primate cognition. Oxford University Press.
(2014). Do artificial reinforcement-learning agents matter morally? CoRR arXiv preprint:1410.8233.
(1915a). Ensayos sobre automática – su definición. Extensión teórica de sus aplicaciones. Revista de la Real Academia de Ciencias Exactas, Físicas y Naturales 12, 391–418. English translation, Randell B., editor. The origins of digital computers. Springer, 1973.
(1915b). Torres and his remarkable automatic devices. Scientific American, 80(2079):296–298.Google Scholar
(2009). The savant syndrome: An extraordinary condition. A synopsis: Past, present, future. Philosophical Transactions of the Royal Society, Series B, 364(1522):1351–1357.Google Scholar
(2006). Binary lambda calculus and combinatory logic. In
and P. M. B. Vitányi Kolmogorov Complexity and Applications, Dagstuhl Seminar Proceedings 6051.
(2009). Differentiation of cognitive abilities across the life span. Developmental Psychology, 45(4):1097.Google Scholar
, , , , and (2005). “Exhibitionists” and “Voyeurs” do it better: A shared environment for flexible coordination with tacit messages. In Environments for multi-agent systems, pages 215–231. Springer.
(1936). On computable numbers, with an application to the entscheidungsproblem. Proceedings of the London Mathematical Society, 2(42):230–265.Google Scholar
(1937). On computable numbers, with an application to the entscheidungsproblem: A correction. Proceedings of the London Mathematical Society, 2(6):544–456.Google Scholar
(1948). Intelligent machinery. Chapter 10 in , editor, The essential Turing: Seminal writings in computing, logic, philosophy, artificial intelligence, and artificial life: Plus the secrets of enigma. Reprint, Oxford University Press, 2004.
(1951). Intelligent machinery, a heretical theory. Chapter 12 in , editor, The essential Turing: Seminal writings in computing, logic, philosophy, artificial intelligence, and artificial life: Plus the secrets of enigma. Reprint, Oxford University Press, 2004.
(1952). Can automatic calculating machines be said to think? BBC Third Programme, 14 and 23 Jan. 1952, between , AMT, and , in , editor, The essential Turing, pp. 494–495. Oxford University Press. http://www.turingarchive.org/browse.php/B/6.
and (1948). Turochamp. In , editor, The essential Turing, pp. 562–575. Oxford University Press.
(2011). Analogy perception applied to seven tests of word comprehension. Journal of Experimental and Theoretical Artificial Intelligence, 23(3):343–362.Google Scholar
and (2012). Multiagent learning: Basics, challenges, and prospects. AI Magazine, 33(3):41.Google Scholar
(2011). The matching pennies tournament. http://matchingpennies.com/ tournament/.
and (2014). Personality in sanctuary-housed chimpanzees: A comparative approach of psychobiological and penta-factorial human models. Evolutionary Psychology, 13(1):182–196.Google Scholar
(1958). Tribute to John von Neumann. Bulletin of the American Mathematical Society, 64(3):1–49.Google Scholar
I.(2008). Machine Intelligence Quotient. VDM.
(2011). Tests of intelligence. In and , editors, The Cambridge handbook of intelligence, pages 20–38. Cambridge University Press.
(2011). Communication with extraterrestrial intelligence. SUNY Press.
(2013). Probably approximately correct: Nature's algorithms for learning and prospering in a complex world. Basic Books.
(2008). Using response times for item selection in adaptive testing. Journal of Educational and Behavioral Statistics, 33(1):5–20.Google Scholar
,, ,
, and , (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review, 113(4): 842.Google Scholar
, , and (2014). Intelligence is what the intelligence test measures. Seriously. Journal of Intelligence, 2(1):12–15.Google Scholar
, , and (2006). Principles of minimal cognition: Casting cognition as sensorimotor coordination. Adaptive Behavior, 14(2):157–170.Google Scholar
A., De , , and (2009). Simple rules can explain discrimination of putative recursive syntactic structures by a songbird species. Proceedings of the National Academy of Sciences, 106(48):20538–20543.Google Scholar
, , and C.(2004). Work group diversity and group performance: An integrative model and research agenda. Journal of Applied Psychology, 89(6):1008.Google Scholar
and Schippers,M. C.(2007).Work group diversity. Annual Review of Psychology, 58:515–541.
, , , , , , , , , and (2013). OpenML: A collaborative science platform. In European Conference on Machine Learning and Knowledge Discovery in Databases, pages 645–649. Lecture Notes in Artificial Intelligence, volume 8190. Springer.
, Van N., , and (2014). Openml: Networked science inmachine learning. ACMSIGKDD Explorations Newsletter, 15(2):49–60.Google Scholar
, , and (1992). The embodied mind: Cognitive science and human experience. MIT Press.
, , , , and (2014). Virtual and real world adaptation for pedestrian detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(4):797–809.Google Scholar
, , , and (2011). A Monte Carlo AIXI approximation. Journal of Artificial Intelligence Research, 40:95–142.Google Scholar
, et al.(1979). Psychological evaluation and testing of children who are deafblind. School Psychology Digest, 8(3):291–295.Google Scholar
(1950). The structure of human abilities.
Methuen.
, , , , and A.(2012). The general factor of personality: A critical test. Personality and Individual Differences, 52(3):261–264.
and (2000). Pigeon reaction time, Hick's law, and intelligence. Psychonomic Bulletin and Review, 7(2):284–291.Google Scholar
and (2014). A survey of personality computing. IEEE Transactions on Affective Computing, 5(3):273–291.Google Scholar
(1993). The coming technological singularity: How to survive in the posthuman era. In Vision 21: Interdisciplinary science and engineering in the era of cyberspace, volume 1, pages 11–22. NASA.
and (1997). On prediction by data compression. In Machine learning:ECML-97, pages 14–30. Springer.
, J., , and (2009).Normalized information distance. In Information theory and statistical learning, pages 45–82. Springer.
(2005). Human computation. PhD thesis, Carnegie Mellon University.
(2009). Human computation. In Design Automation Conference, 2009. DAC-09. 46th ACM/IEEE, pages 418–419. IEEE.
, , and (2004). Telling humans and computers apart automatically. Communications of the ACM, 47(2):56–60.Google Scholar
, , , , and (2008). RECAPTCHA: Human-based character recognition via web security measures. Science, 321(5895):1465.Google Scholar
(1966). Theory of self-reproducing automata. , editor. University of Illinois Press.
and (2012). Bears ‘count’ too: Quantity estimation and comparison in black bears. Ursus americanus. Animal Behaviour, 84(1):231–238.Google Scholar
(2007). Essentials of general intelligence: The direct path to artificial general intelligence. In and , editors Artificial general intelligence, pages 131–157. Springer.
(1978). Mind in society: The development of higher psychological processes. Harvard University Press.
(2000). Computerized adaptive testing: A primer, 2nd edition. Lawrence Erlbaum Associates.
(1870). The limits of natural selection as applied toman. In Contributions to the theory of natural selection, pages 332–371. Macmillan.
(1904). Man's place in the universe. Chapman and Hall.
(1964). A suggestion for a fast multiplier. IEEE Transactions on Electronic Computers, EC-13(1):14–17.Google Scholar
(2005). Statistical and inductive inference by minimum message length. Springer.
and M.(1968). An information measure for classification. Computer Journal, 11(2):185–194.Google Scholar
and , (1999). Minimum message length and Kolmogorov complexity. Computer Journal, 42(4):270–283.Google Scholar
, , , , , , and (2012). Social Turing tests: Crowdsourcing sybil detection. CoRR arXiv preprint:1205.3856.
, , , and Y.(2014). Man vs. machine: Practical adversarial detection of malicious crowdsourcing workers. In 23rd USENIX Security Symposium, USENIX Association, CA, pages 239–254. USENIX Association.
, , , , and Liu, T.-Y.(2015). Solving verbal comprehension questions in IQ test by knowledge-powered word embedding. CoRR arXiv preprint:1505.07909.
(2009a). Behavioral biometrics for human identification: Intelligent applications. IGI Global.
(2010). The evaluation of AGI systems. In , , and , editors, 3rd Conference on Artificial General Intelligence, pages 164–169. Atlantis Press.
(2009b). On abstract intelligence: Toward a unifying theory of natural, artificial, machinable, and computational intelligence. International Journal of Software Science and Computational Intelligence, 1(1):1–17.Google Scholar
(2000). QI: The quest for intelligence. Piatkus.
(2014). Turing Test success marks milestone in computing history. University or Reading Press Release, 8 June.
and R.(2006). Comparative cognition: Experimental explorations of animal intelligence. Oxford University Press.
(1972). Pattern recognition as information compression. In Frontiers of pattern recognition, pages 561–567. Academic Press.
(2006). Multiple intelligences, the Mozart effect, and emotional intelligence: A critical review. Educational Psychologist, 41(4):207–225.Google Scholar
(1967). Behavior: An introduction to comparative psychology.Henry Holt.
(2008). Can people think? Or machines? A unified protocol for Turing testing. In , , and , editors, Parsing the Turing test: Philosophical and methodological issues in the quest for the thinking computer, pages 301–318. Springer.
(2009). Animals versus animats: Or why not model the real iguana. Adaptive Behavior, 17(4):269–286.Google Scholar
(1944). The measurement of intelligence. Williams and Wilkins.
(2008).WechslerAdult Intelligence Scale–fourth edition (WAIS-IV). NCS Pearson.
and (2016). The mind club: Who thinks, what feels, and why it matters. Viking.
(2011). Better data from better measurements using computerized adaptive testing. Journal of Methods and Measurement in the Social Sciences, 2(1):1–27.Google Scholar
and (1999).What is ‘multi’ in multi-agent learning. In , editor, Collaborative learning: Cognitive and computational approaches, pages 64–80. Pergamon Press.
(1966). ELIZA – a computer program for the study of natural language communication between man and machine. Communications of the ACM, 9(1):36–45.Google Scholar
, , , and (2004). Price prediction in a trading agent competition. Journal of Artificial Intelligence Research, 21:19–36.Google Scholar
(2000). Autonomous mental development and performance metrics for intelligent systems. In
, editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMIS Workshop, pages 349–358. NIST Special Publication 970. NIST.
(2009). Task muddiness, intelligence metrics, and the necessity of autonomous mental development. Minds and Machines, 19(1):93–115.Google Scholar
(2013). Natural and artificial intelligence: Introduction to computational brain- mind. BMI Press.
, , , , , , and (2001). Autonomous mental development by robots and animals. Science, 291(5504):599–600.Google Scholar
, , , and (2015). Towards AI-complete question answering: A set of prerequisite toy tasks. CoRR arXiv preprint:1502.05698.
and (2005). On the role of environments in multiagent systems. Informatica, 29(4):409–421.Google Scholar
(1847). The philosophy of the inductive sciences. Reprint, Cambridge University Press, 2014.
(1996). Why the Turing test: AI's biggest blind alley. In and , editors, Machines and thought: The legacy of Alan Turing), pp. 53–63. Oxford University Press.
, , , , W., , , , and (2013). Better GP benchmarks: Community survey results and proposals. Genetic Programming and Evolvable Machines, 14:3–29.Google Scholar
and , (1997). Machiavellian intelligence II: Extensions and evaluations, volume 2. Cambridge University Press.
, , , and (2009). Emulation, imitation, over-imitation and the scope of culture for child and chimpanzee. Philosophical Transactions of the Royal Society, Series B, 364(1528):2417–2428.Google Scholar
, , , and (2011). Protecting against evaluation overfitting in empirical reinforcement learning. In Adaptive dynamic programming and reinforcement learning (ADPRL), pages 120–127. IEEE.
(2005). QV (ƛ)-learning: A new on-policy reinforcement learning algorithm. In , editor, 7th European Workshop on Reinforcement Learning, pages 17–18. EWRL.
(1973). Personality and prediction: Principles of personality assessment. Addison-Wesley.
and (1989). Test of Language Competence (TLC), expanded edition. Psychological Corporation.
(2005). Measuring reasoning ability. In Handbook of understanding and measuring intelligence, pages 373–392. Sage.
(1668). An essay towards a real character, and a philosophical language. S. Gellibrand.
(2012). Robot social intelligence. In , , , , and , editors, Proceedings for the 4th International Conference Social Robotics, ICSR 2012, pages 45–55. Lecture Notes in Computer Science, volume 7621. Springer.
and , (2010). Information dynamics of evolved agents. In From Animals to Animats 11, pages 38–49. Springer.
, , , and , (2007). Intense ultrasonic clicks from echolocating toothed whales do not elicit anti-predator responses or debilitate the squi. Loligo pealeii. Biology Letters, 3(3):225–227.Google Scholar
(1991). The animat path to AI. In Meyer, J.-A. and , editors, From animals to animats, pages 15–21. MIT Press.
and (1983). Beliefs about beliefs: Representation and constraining function of wrong beliefs in young children's understanding of deception. Cognition, 13(1):103–128.Google Scholar
(2002). A new kind of science. Wolfram Media.
(1996). The lack of a priori distinctions between learning algorithms. Neural Computation, 8(7):1341–1390.Google Scholar
(2012). What the no free lunch theorems really mean; how to improve search algorithms. Technical Report. Santa Fe Institute.
and , (1995). No free lunch theorems for search. Technical Report, SFI-TR-95-02-010. Santa Fe Institute.
and , (2005). Coevolutionary free lunches. IEEE Transactions on Evolutionary Computation, 9(6):721–735.Google Scholar
and (2011). Is collective intelligence (mostly) the general factor of personality? A comment on Woolley, Chabris, Pentland, Hashmi and Malone(2010). Intelligence, 39(2):79–81.Google Scholar
, , and , (2015). The more g-loaded, the more heritable, evolvable, and phenotypically variable: Homology with humans in chimpanzee cognitive abilities. Intelligence, 50:159–163.Google Scholar
, , , , and L.(2005). Is this robot like me? Links between human and robot personality traits. In 5th IEEE-RAS International Conference on Humanoid Robots, pages 375–380. IEEE.
, , , , and , (2010). Evidence for a collective intelligence factor in the performance of human groups. Science, 330(6004):686–688.Google Scholar
WPSA(2014). Universal declaration on animal welfare (UDAW).World Society for the Protection of Animals. http://www.udaw.org/.
and (2007). Metrics for cognitive architecture evaluation. In , editor, Proceedings of the AAAI-07 Workshop on Evaluating Architectures for Intelligence, pages 60–66. AAAI.
(1932). The roles of mutation, inbreeding, crossbreeding, and selection in evolution. In Proceedings of the VI International Congress of Genetics, pages 356–366. Botanic Garden, New York.
(2012). AI-complete, AI-hard, or AI-easy–classification of problems in AI. In The 23rd Midwest Artificial Intelligence and Cognitive Science Conference, pages 94-101.
(2015a). Artificial superintelligence: A futuristic approach. CRC Press.
(2015b). The space of possible mind designs. In , , and , editors, 8th International Conference on Artificial general intelligence – AGI 2015, Berlin, Germany, July 22–25, 2015, Proceedings, pages 218–227. Springer.
and L.(2012). Artimetrics: Biometrics for artificial entities. Robotics and Automation Magazine, 19(4):48–58.Google Scholar
and (2008). Behavioural biometrics: A survey and classification. International Journal of Biometrics, 1(1):81–113.Google Scholar
(2005). Information theory, evolution, and the origin of life. Cambridge University Press.
(2012). Toward a standard metric of machine intelligence. World Future Review, 4(2):61–70.Google Scholar
and (2012). Taking Turing seriously (but not literally). In and , editors, AISB/IACAP 2012 Symposium “Revisiting Turing and His Test”, pages 54–59. Society for the Study of Artificial Intelligence and Simulation of Behaviour.
, , and (2015). Computer-based personality judgments are more accurate than those made by humans. Proceedings of the National Academy of Sciences, 112(4):1036–1040.Google Scholar
, , , , , , , and (2016). Intelligence-augmented rat cyborgs in maze solving. PloS ONE, 11(2):e0147754.
(2008). Artificial intelligence as a positive and negative factor in global risk. Global Catastrophic Risks, 1:303.Google Scholar
(1994). Fuzzy logic, neural networks, and soft computing. Communications of the ACM, 37(3):77–84.Google Scholar
(2000). The search for metrics of intelligence–a critical view. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMISWorkshop, pages 105–111. NIST Special Publication 970. NIST.
(2002). In quest of performance metrics for intelligent systems – A challenge that cannot be met with existing methods. In and , editors, Measuring the performance and intelligence of systems: Proceedings of the 2000 PerMISWorkshop, pages 303–306. NIST Special Publication 970. NIST.
(2008). Toward human level machine intelligence – Is it achievable? The need for a paradigm shift. IEEE Computational Intelligence Magazine, 3(3):11–22.Google Scholar
and (2009). Learning mazes with aliasing states: An LCS algorithm with associative perception. Adaptive Behavior, 17(1):28–57.Google Scholar
(2012). Perspectives on observational learning in animals. Journal of Comparative Psychology, 126(2):114.Google Scholar
, , and , (1980). Oddity learning in the pigeon: Effect of negative instances, correction, and number of incorrect alternatives. Animal Learning and Behavior, 8(4):621–629.Google Scholar
, , and (1974). Comparison of two oddity tasks with pigeons. Learning and Motivation, 5(1):106–117.Google Scholar
, , , and C.(2011). Crowdsourcing general computation. In Proceedings of ACM CHI Conference on Human Factors. ACM.
(2012). My robot is smarter than your robot: On the need for a total Turing test for robots. In and , editors, AISB/IACAP 2012 Symposium “Revisiting Turing and His Test”, pages 12–15. Society for the Study of Artificial Intelligence and Simulation of Behaviour.
, , and , (2015). Gödel agents in a scalable synchronous agent framework. In , , and , editors, 8th International Conference on Artificial general intelligence, pages 404–413. Springer.
, , , , , and (2016). Measuring machine intelligence through visual question answering. AI Magazine, 37(1):63–72.Google Scholar
(2000). Interspecies semantic communication in two forest primates. Proceedings of the Royal Society of London, Series B, 267(1444):713–718.Google Scholar
and , (1970). The complexity of finite objects and the development of the concepts of information and randomness by means of the theory of algorithms. Russian Mathematical Surveys, 25:83–124.Google Scholar
and , (1998). Situation models in language comprehension and memory. Psychological Bulletin, 123(2):162.Google Scholar