Cognitive Choice Modeling PDF

by Zheng Joyce Wang, Jerome R. Busemeyer

Part of the The MIT Press series

PDF

Download - Immediately Available

Please note: eBooks can only be purchased with a UK issued credit card and all our eBooks (ePub and PDF) are DRM protected.

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.