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An Application of ASP Theories of Intentions to Understanding Restaurant Scenarios: Insights and Narrative Corpus



This paper presents a practical application of Answer Set Programming to the understanding of narratives about restaurants. While this task was investigated in depth by Erik Mueller, exceptional scenarios remained a serious challenge for his script-based story comprehension system. We present a methodology that remedies this issue by modeling characters in a restaurant episode as intentional agents. We focus especially on the refinement of certain components of this methodology in order to increase coverage and performance. We present a restaurant story corpus that we created to design and evaluate our methodology.



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We would like to thank Zengzhi Jiang, Keya Patel, and Marcello Balduccini for their help in retrieving excerpts from Google Books and Project Gutenberg.



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Balduccini, M. 2007. CR-MODELS: An inference engine for CR-Prolog. In Proceedings of LPNMR 2007, Baral, C., Brewka, G., and Schlipf, J. S., Eds. LNCS, vol. 4483. Springer, 1830.
Balduccini, M. and Gelfond, M. 2003. Logic programs with consistency-restoring rules. In Proceedings of Commonsense-03. AAAI Press, 918.
Balduccini, M. and Gelfond, M. 2008. The AAA architecture: An overview. In Architectures for Intelligent Theory-Based Agents, Papers from the 2008 AAAI Spring Symposium, 2008. AAAI Press, 1–6.
Baral, C. and Gelfond, M. 2000. Reasoning Agents in Dynamic Domains. Kluwer Academic Publishers, Norwell, MA, 257279.
Baral, C. and Gelfond, M. 2005. Reasoning about intended actions. In Proceedings of AAAI-05, AAAI Press, 689694.
Barr, A. and Feigenbaum, E. 1981. The Handbook of Artificial Intelligence. vol. 1. William Kaufman Inc., Los Altos, CA.
Bertelsen, O. W. and Bødker, S. 2003. Activity theory. In HCI Models, Theories, and Frameworks: Toward a Multidisciplinary Science. Morgan Kaufmann, San Francisco, CA, 291324.
Blount, J. 2013. An Architecture for Intentional Agents. Ph.D. thesis, Texas Tech University, Lubbock, TX, USA.
Blount, J., Gelfond, M. and Balduccini, M. 2015. A theory of intentions for intelligent agents. In Proceedings of LPNMR 2015, Calimeri, F., Ianni, G., and Truszczynski, M., Eds. LNCS, vol. 9345. Springer, 134142.
Bratman, M. 1987. Intentions, Plans, and Practical Reason. Harvard University Press, Cambridge, MA.
Chambers, N. and Jurafsky, D. 2008. Unsupervised learning of narrative event chains. In Proceedings of ACL-08: HLT. 789797.
Craik, K. J. W. 1943. The Nature of Explanation. Cambridge University Press, Cambridge, UK.
Gabaldon, A. 2009. Activity recognition with intended actions. In Proceedings of IJCAI 2009, Boutilier, C., Ed. 1696–1701.
Gelfond, M. and Kahl, Y. 2014. Knowledge Representation, Reasoning, and the Design of Intelligent Agents. Cambridge University Press, Cambridge, UK.
Gordon, A. S., Cao, Q. and Swanson, R. 2007. Automated story capture from internet weblogs. In Proceedings of the 4th International Conference on Knowledge Capture. K-CAP ’07. ACM, New York, NY, USA, 167168.
Gupta, R. and Kochenderfer, M. J. 2004. Common sense data acquisition for indoor mobile robots. In Proceedings of the 19th National Conference on Artificial Intelligence. AAAI’04. AAAI Press, 605610.
Hoos, H. H., Kaufmann, B., Schaub, T. and Schneider, M. 2013. Robust benchmark set selection for Boolean constraint solvers. In 7th International Conference on Learning and Intelligent Optimization (LION-13) – Revised Selected Papers. Springer-Verlag, New York, NY, USA, 138152.
Inclezan, D. and Gelfond, M. 2011. Representing biological processes in modular action language ALM. In Proceedings of Commonsense 2011, 4955.
Inclezan, D., Zhang, Q., Balduccini, M. and Israney, A. 2017. Understanding restaurant stories using an ASP theory of intentions (extended abstract). In Technical Communications of the 33rd International Conference on Logic Programming (ICLP-TC 2017). OASIcs.
Inclezan, D., Zhang, Q., Balduccini, M. and Israney, A. 2018. An ASP methodology for understanding narratives about stereotypical activities. Theory and Practice of Logic Programming 18, 3–4, 535552.
Johansson, R. and Nugues, P. 2007a. Language Technology at LTH. [Accessed March 15, 2019].
Johansson, R. and Nugues, P. 2007b. LTH: Semantic structure extraction using nonprojective dependency trees. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007). Association for Computational Linguistics, Prague, Czech Republic, 227230.
Johnson-Laird, P. N. 1983. Mental Models: Toward a Cognitive Science of Language, Inference, and Consciousness. Harvard University Press, Cambridge, MA.
Manning, C. D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S. J. and McClosky, D. 2014. Stanford CoreNLP a suite of core NLP tools. [Accessed on March 15, 2019].
Manshadi, M., Swanson, R. and Gordon, A. S. 2008. Learning a Probabilistic Model of Event Sequences from Internet Weblog Stories. In 21st Conference of the Florida AI Society (FLAIRS), Applied Natural Language Processing Track. Coconut Grove, FL.
Modi, A., Anikina, T., Ostermann, S. and Pinkal, M. 2017. Narrative texts annotated with script information. In Proceedings of the Tenth Edition of the Language Resources and Evaluation Conference. European Language Resources Association, 3485–3493. CoRRabs/1703.05260 [Accessed on March 15, 2019].
Mueller, E. T. 2004. Understanding script-based stories using commonsense reasoning. Cognitive Systems Research 5, 4, 307340.
Mueller, E. T. 2007. Modelling space and time in narratives about restaurants. Literary and Linguistic Computing 22, 1, 6784.
Ng, H. T. andMooney, R. J. 1992. Abductive plan recognition and diagnosis: A comprehensive empirical evaluation. In Proceedings of the 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR’92), October 25–29, 1992, Cambridge, MA, 499508.
Regneri, M., Koller, A. and Pinkal, M. 2010. Learning script knowledge with web experiments. In Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics. ACL ’10. Association for Computational Linguistics, Stroudsburg, PA, USA, 979988.
Schank, R. C. and Abelson, R. P. 1977. Scripts, Plans, Goals, and Understanding: An Inquiry into Human Knowledge Structures. Lawrence Erlbaum.
Shanahan, M. 1997. Solving the Frame Problem. MIT Press.
Singh, P., Lin, T., Mueller, E. T., Lim, G., Perkins, T. and Zhu, W. L. 2002. Open mind common sense: Knowledge acquisition from the general public. In On the Move to Meaningful Internet Systems, 2002 – DOA/CoopIS/ODBASE 2002. Springer-Verlag, London, UK, 12231237.
Smith, D. and Arnold, K. C. 2009. Learning hierarchical plans by reading simple English narratives. In Proceedings of the Commonsense Workshop at IUI-09.
van Dijk, T. A. and Kintsch, W. 1983. Strategies of Discourse Comprehension. Academic Press, Orlando, FL.
Zhang, Q. and Inclezan, D. 2017. An application of ASP theories of intentions to understanding restaurant scenarios. In Proceedings of PAoASP’17.


An Application of ASP Theories of Intentions to Understanding Restaurant Scenarios: Insights and Narrative Corpus



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