Computational Psychology

by

Ron Sun

• LAST REVIEWED: 27 October 2022
• LAST MODIFIED: 27 October 2022
• DOI: 10.1093/obo/9780199828340-0299

Introduction

Computational psychology is concerned with understanding the mind and its various functions and domains through developing detailed, mechanistic, process-based models, namely, computational (in a broad sense) models of representations, mechanisms, and processes. It embodies theories in computer algorithms and programs, which are in turn based on artificial intelligence and computer science. That is, it imputes computational processes onto psychological functions, and thereby it produces runnable computational models. Detailed simulations can then be conducted based on computational models. Empirical disciplines, such as cognitive psychology, social psychology, and developmental psychology, provide empirical data, findings, phenomena, ideas, and other information to computational psychology. Computational psychologists then analyze and abstract them to form coherent theories in computational forms. In turn, these theories impact other disciplines, including those disciplines from which they draw their initial inspirations. Thus, work in computational psychology relies on empirical work from various empirical disciplines, and work in other disciplines in turn is influenced by work from computational psychology. Note that computational models are, mostly, “process theories”—that is, they are meant to answer the question of how human performance and behavior comes about; by what psychological mechanisms, processes, representations, and knowledge; and in what ways exactly. In contrast, it is also possible to formulate “product theories” that provide a functional account of the phenomena but do not commit to a particular psychological mechanism or process. This article emphasizes the former. Note also that, because of the existence of many different or even conflicting viewpoints, paradigms, and theories, this article can only provide a sparse sampling of perspectives and models (especially with regard to various specific psychological or cognitive domains), not exhaustive or complete in any way. The reader should explore further and make up their own mind about various perspective and models.

General Overviews

Bechtel and Graham 1998; Boden 2006; Busemeyer, et al. 2015; Chipman 2017; and Sun 2008 provide the reader with a general and broad overview of computational psychology. Some of them may cover more than just computational psychology and some others may cover less than the full scope of computational psychology. Nevertheless, these are the best existing publications in terms of providing a general overview.

• Bechtel, W., and G. Graham, eds. 1998. A companion to cognitive science. Malden, MA, and Oxford: Blackwell.

  This is an old collection of articles on cognitive science, with some coverage of computational modeling, that is, computational psychology. It may be of interest for historical reasons.

• Boden, M. 2006. Mind as machine: A history of cognitive science. 2 vols. Oxford: Clarendon Press.

  This two-volume work is a historical overview of cognitive science, which includes computational cognitive modeling (i.e., computational psychology).

• Busemeyer, J. R., Z. Wang, J. T. Townsend, and A. Eidels, eds. 2015. The Oxford handbook of computational and mathematical psychology. New York: Oxford Univ. Press.

  Some of the articles in this volume survey areas in computational psychology.

• Chipman, S., ed. 2017. The Oxford handbook of cognitive science. New York: Oxford Univ. Press.

  Some of the articles in this handbook cover domains of computational psychology. The book, as a whole, may serve to provide a broad perspective on and the context for computational psychology.

• Sun, R., ed. 2008. The Cambridge handbook of computational psychology. New York: Cambridge Univ. Press.

  Thus far, this volume is the latest and the most comprehensive handbook in computational psychology. It covers a broad range of domains, as well as modeling techniques, written by top experts in these domains.