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Abstract

A comprehensive and authoritative review on most important developments in computational and mathematical psychology that have impacted many other fields in past decades. Written in tutorial style by leading scientists in each topic area, with an emphasis on examples and applications. Each chapter is self-contained and aims to engage readers with various levels of modeling experience. The Handbook covers the key developments in elementary cognitive mechanisms (e.g., signal detection, information processing, reinforcement learning), basic cognitive skills (e.g., perceptual judgment, categorization, episodic memory), higher-level cognition (e.g., Bayesian cognition, decision making, semantic memory, shape perception), modeling tools (e.g., Bayesian estimation and other new model comparison methods), and emerging new directions (e.g., neurocognitive modeling, applications to clinical psychology, quantum cognition) in computation and mathematical psychology. The chapters were written for a typical graduate student in virtually any area of psychology, cognitive science, and related social and behavioral sciences, such as consumer behavior and communication. We also expect it to be useful for readers ranging from advanced undergraduate students to experienced faculty members and researchers. Beyond being a handy reference book, it should be beneficial as a textbook for self-teaching, and for graduate level (or advanced undergraduate level) courses in computational and mathematical psychology.

The Oxford Handbook of Computational and Mathematical Psychology
 

Jerome R. Busemeyer (ed.), Zheng Wang (ed.)James T. Townsend (ed.)Ami Eidels (ed.)

Description

The emerging interdisciplinary field of cognitive choice models integrates theory and recent research findings from both decision process and choice behavior.

Cognitive decision processes provide the interface between the environment and brain, enabling choice behavior, and the basic cognitive mechanisms underlying decision processes are fundamental to all fields of human activity. Yet cognitive processes and choice processes are often studied separately, whether by decision theorists, consumer researchers, or social scientists. In Cognitive Choice Modeling, Zheng Joyce Wang and Jerome Busemeyer introduce a new cognitive modeling approach to the study of human choice behavior. Integrating recent research findings from both cognitive science and choice behavior, they lay the groundwork for the emerging interdisciplinary field of cognitive choice modeling.

The authors focus on individual choice behavior. They begin with a survey of decision science, covering such areas as utility theory, random utility models, and statistical methods for estimating and comparing choice models. They then introduce recent cognitive psychology theories on signal detection and sequential sampling in decision-making. They cover applications of sequential sampling models to both evidence-based and value-based decisions. Their discussion of recent theoretical findings on the integration of learning and choice includes the differences between model-free and model-based learning theories. Having presented the foundational behavioral findings, they move on to the rapid progress being made toward understanding the relations between cognitive choice models and the neural mechanisms underlying choice behavior. Finally, they examine new research directions, including process models based on quantum probability principles.

Cognitive Choice Modeling

  Zheng Joyce Wang and Jerome R. Busemeyer

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