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The Cambridge Handbook of Cognitive Science
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Book description

Cognitive science is a cross-disciplinary enterprise devoted to understanding the nature of the mind. In recent years, investigators in philosophy, psychology, the neurosciences, artificial intelligence, and a host of other disciplines have come to appreciate how much they can learn from one another about the various dimensions of cognition. The result has been the emergence of one of the most exciting and fruitful areas of inter-disciplinary research in the history of science. This volume of original essays surveys foundational, theoretical, and philosophical issues across the discipline, and introduces the foundations of cognitive science, the principal areas of research, and the major research programs. With a focus on broad philosophical themes rather than detailed technical issues, the volume will be valuable not only to cognitive scientists and philosophers of cognitive science, but also to those in other disciplines looking for an authoritative and up-to-date introduction to the field.


‘Many of the papers will serve as ideal introductions to their given domains and, taken collectively, readers will be given a broad grounding in this fascinating area of study.’

Sam Clarke Source: Philosophical Psychology

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  • 8 - Concepts
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    This chapter provides empirical and theoretical understanding of cognition. Today localizationism dominates neuroscience, ranging from single cell recording to functional magnetic resonance imaging (FMRI), while anti-localizationism has a new home in dynamical systems modeling. Cognitive science encompasses both. It is sometimes said that the cognitive revolution stemmed from seizing on a new technology, the digital computer, as a metaphor for the mind. Artificial neural network represents a counterpoint to discrete computation. Symbolic architectures share a commitment to representations whose elements are symbols and operations on those representations that typically involve moving, copying, deleting, comparing, or replacing symbols. The chapter highlights just two trends: the expansion of inquiry down into the brain (cognitive neuroscience) and out into the body and world (embedded and extended cognition). The expansion outward has been more diverse, but the transitional figure clearly is James J. Gibson.
  • 9 - Language
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    The phrase "the Representational Theory of Mind" (RTM) is used in two different but related ways. To understand the difference, one must distinguish two levels at which human beings can be described. The first is personal and belongs to common sense or folk psychology. The second level, in contrast, is subpersonal and scientific. Cognitive scientists and philosophers of cognitive science have offered various characterizations. This chapter begins with the author's own view, based on C.S. Peirce's general theory of representation, and then uses that as a basis of comparison to other views. Cognitive scientists, who conceptualize the mind/brain as, or as substantially like, a computer, take the representation-bearers of mental representations to be computational structures or states. Peirce hypothesized two broad kinds of ground for representation: similarity and causation. Mental representations play multiple roles in cognitive science explanations, which themselves come in many kinds.
  • 10 - Emotion
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    This chapter reviews the two main current approaches to cognitive architecture: rule-based systems and connectionism. Both kinds of architecture assume the central hypothesis of cognitive science that thinking consists of the application of computational procedures to mental representations, but they propose very different kinds of representations and procedures. Both rule-based and connectionist architectures have had many successes in explaining important psychological phenomena concerning problem solving, learning, language use, and other kinds of thinking. Given their large and only partially overlapping range of explanatory applications, it seems unlikely that either of the two approaches to cognitive architecture will come to dominate cognitive science. The chapter suggests a reconciliation of the two approaches by means of theoretical neuroscience. Unified understanding of how the brain can perform both serial problem solving using rules and parallel constraint satisfaction using distributed representations will be a major triumph of cognitive science.
  • 12 - Cognitive neuroscience
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    This chapter surveys some recent philosophical and empirical work on the nature and structure of action, on conscious agency, and on our knowledge of actions. By reuniting the causal approach with the rational approach, the causalists opened the way for a naturalistic stance in action theory and thus for an integration of philosophical and scientific enquiries. Many philosophers introduce a conception of intentions as distinctive, sui generis, mental states. Intentions are responsible for triggering or initiating the intended action (initiating function) and for guiding its course until completion. Dual-intention theories provide a partial answer to the problem of causal deviance. The chapter concentrates on the functional architecture of motor cognition, introducing some of the theoretical concepts, models, and hypotheses that play a central role in current thinking in the motor domain and are of particular relevance for philosophical theorizing on action.
  • 13 - Evolutionary psychology
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    This chapter provides a brief introduction to the modern science of memory and presents some significant issues in the field. The contributions of Hermann Ebbinghaus, Frederick Bartlett, and Brenda Milner reveals important insights into how memory works, and the chapter draws upon each approach in characterizing the functional organization of human memory. One of the most significant questions in memory research has been whether there is a fundamental difference between the retention of information across short delays versus long delays. Working memory (WM) model proposes a separation between short-term storage (or maintenance) and the manipulation of information in the service of task goals. Successful memory performance depends not only on how information is encoded, but also on interactions between encoding and retrieval processes. Forgetting can occur even for information that was adequately processed at encoding. Consolidation theory and interference theory are the most popular accounts of forgetting.
  • 14 - Embodied, embedded, and extended cognition
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    This chapter introduces some recent developments in the areas of human reasoning and decision making. Regarding decision making, the chapter focuses on decision-under-risk, using problems which are explicitly described in linguistic or symbolic terms. Human common-sense reasoning is far more sophisticated than any current artificial intelligence models can capture; yet people's performance on, for example, simple conditional inference, while perhaps explicable in probabilistic terms, is by no means effortless and noise-free. It may be that human reasoning and decision making function best in the context of highly adapted cognitive processes such as basic learning, deploying world knowledge, or perceptuomotor control. Indeed, what is striking about human cognition is the ability to handle, even to a limited extent, reasoning and decision making in novel, hypothetical, verbally stated scenarios, for which our past experience and evolutionary history may have provided us with only minimal preparation.
  • 15 - Animal cognition
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    This chapter reviews basic findings of the psychology of concepts that are the basis for two very different strands of research that investigate concepts, one focusing on formal aspects of categories and studying artificial category learning, the other focusing on the content of concepts and how learning and judgment interact with prior knowledge. Then it discusses formal models of category learning, including D.L. Medin and M.M. Schaffer's context model (CM). The formal models of category learning are turning to mixtures of different processes, with the hope that they can predict when one form of learning (rule testing, prototype extraction, exemplar learning) is preferred. Transitioning toward the second strand, the chapter discusses how higher-level knowledge influences the category learning task, suggesting that a broader approach may be required. Finally, the chapter moves completely to the second strand and reviews work on conceptual development, essentialism, and knowledge effects.
  • Glossary
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    This chapter integrates linguistic theory with more general concerns of cognitive science. In the context of cognitive science, language is best thought of as a cognitive system within an individual's brain that relates certain aspects of thought to acoustic signals. In order to appreciate the sophistication of the child's achievement in acquiring language, it is useful to examine all the structure associated with a very simple fragment of English such as the phrase "those purple cows". A major line of approach to linguistic combinatoriality, embracing a wide range of theories, is specifically built around the combinatorial properties of linguistic structure. The regular rules of grammar, like words, idioms, and meaningful constructions, are pieces of structure stored in long-term memory. A debate of over twenty years' standing concerns the distinction between regular and irregular morphological forms in language. Most experimental work on sentence processing concerns speech perception.


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