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48 results

Page 1 of 3

  • 1 - An Overview of Computational Cognitive Sciences

  • from Part I - Introduction
  • Edited by Ron Sun, Rensselaer Polytechnic Institute, New York
  • Book: The Cambridge Handbook of Computational Cognitive Sciences
  • Published online: 21 April 2023
  • Print publication: 11 May 2023, pp 3-26

  • Summary

    This chapter provides an introduction and an overview of computational cognitive sciences. Computational cognitive sciences explore the essence of cognition and various cognitive functionalities through developing mechanistic, process-based understanding by specifying corresponding computational models. These models impute computational processes onto cognitive functions and thereby produce runnable programs. Detailed simulations and other operations can then be conducted. Understanding the human mind strictly from observations of, and experiments with, human behavior is ultimately untenable. Computational modeling is therefore both useful and necessary. Computational cognitive models are theoretically important because they represent detailed cognitive theories in a unique, indispensable way. Computational cognitive modeling has thus far deepened the understanding of the processes and the mechanisms of the mind in a variety of ways.

  • 32 - Cognitive Modeling in Social Simulation

  • from Part IV - Computational Modeling in Various Cognitive Fields
  • Edited by Ron Sun, Rensselaer Polytechnic Institute, New York
  • Book: The Cambridge Handbook of Computational Cognitive Sciences
  • Published online: 21 April 2023
  • Print publication: 11 May 2023, pp 1064-1087

  • Summary

    This chapter discusses cognitive social simulation, which lies at the intersection of cognitive modeling and social simulation – two forms of computational modeling. Cognitive modeling focuses on producing precise computational models of individual mental processes, while social simulation centers on models of social processes (such as interaction of individuals or collective decision making). By combining cognitive and social models, cognitive social simulation is poised to address issues concerning both individuals and society. Detailed simulation enables precise analysis of possible scenarios and outcomes (social or individual). A number of examples of cognitive social simulation are sketched in this chapter. Issues involved are discussed. Some promising directions are outlined.

The Cambridge Handbook of Computational Cognitive Sciences
  • 2nd edition
  • Edited by Ron Sun
  • Published online: 21 April 2023
  • Print publication: 11 May 2023
  • The Cambridge Handbook of Computational Cognitive Sciences is a comprehensive reference for this rapidly developing and highly interdisciplinary field. Written with both newcomers and experts in mind, it provides an accessible introduction of paradigms, methodologies, approaches, and models, with ample detail and illustrated by examples. It should appeal to researchers and students working within the computational cognitive sciences, as well as those working in adjacent fields including philosophy, psychology, linguistics, anthropology, education, neuroscience, artificial intelligence, computer science, and more.

  • 5 - Connectionism and neural networks

    • By Ron Sun, Rensselaer Polytechnic Institute
  • Edited by Keith Frankish, The Open University, Milton Keynes, William M. Ramsey, University of Nevada, Las Vegas
  • Book: The Cambridge Handbook of Artificial Intelligence
  • Published online: 05 July 2014
  • Print publication: 12 June 2014, pp 108-127

  • Summary

    This chapter reviews briefly the history of connectionist models, identifying major ideas and major areas of applications. It gives a brief review of major paradigms of learning in neural networks. The chapter addresses the issue of symbolic processing in connectionist models. It looks in particular at the following types of learning: supervised learning, unsupervised learning, and reinforcement learning. The connectionist revolution has spurred vigorous theoretical debates about the nature of cognition and the various approaches toward understanding. The chapter discusses the hybrid connectionist models, which incorporate both connectionist and symbolic processing methods. In contrast to connectionist implementationism, hybrid connectionist models may be considered a synthesis of connectionist models and traditional symbolic models. Hybrid models, such as CLARION, have been used to address a wide variety of issues in cognitive science and artificial intelligence, including human learning, reasoning, problem solving, creativity, motivational dynamics, metacognitive processes, and above all, human consciousness.

  • 1 - Introduction to Computational Cognitive Modeling

  • from Part I - Introduction
  • Edited by Ron Sun
  • Book: The Cambridge Handbook of Computational Psychology
  • Published online: 05 June 2012
  • Print publication: 28 April 2008, pp 3-20

  • Summary

    This chapter provides an overview of the book on Introduction to Computational Cognitive Modeling. The first part of the book provides a general introduction to the field of computational cognitive modeling. The second part, Cognitive Modeling Paradigms, introduces the reader to broadly influential approaches in cognitive modeling. The third part, Computational Modeling of Various Cognitive Functionalities and Domains, describes a range of computational modeling efforts that researchers in this field have undertaken regarding major cognitive functionalities and domains. This part surveys and explains computational modeling research, in terms of detailed computational mechanisms and processes, on memory, concepts, learning, reasoning, decision making, skills, vision, motor control, language, development, scientific explanation, social interaction, and so on. The final part, Concluding Remarks, explores a range of issues associated with computational cognitive modeling and cognitive architectures, and provides some perspectives, evaluations, and assessments.

The Cambridge Handbook of Computational Psychology
  • Edited by Ron Sun
  • Published online: 05 June 2012
  • Print publication: 28 April 2008
  • This book is a definitive reference source for the growing, increasingly more important, and interdisciplinary field of computational cognitive modeling, that is, computational psychology. It combines breadth of coverage with definitive statements by leading scientists in this field. Research in computational cognitive modeling explores the essence of cognition and various cognitive functionalities through developing detailed, process-based understanding by specifying computational mechanisms, structures, and processes. Given the complexity of the human mind and its manifestation in behavioral flexibility, process-based computational models may be necessary to explicate and elucidate the intricate details of the mind. The key to understanding cognitive processes is often in fine details. Computational models provide algorithmic specificity: detailed, exactly specified, and carefully thought-out steps, arranged in precise yet flexible sequences. These models provide both conceptual clarity and precision at the same time. This book substantiates this approach through overviews and many examples.

Page 1 of 3