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Can quantum probability provide a new direction for cognitive modeling?

Published online by Cambridge University Press:  14 May 2013

Emmanuel M. Pothos  and
Jerome R. Busemeyer
Emmanuel M. Pothos
Affiliation:
Department of Psychology, City University London, London EC1V 0HB, United Kingdom. emmanuel.pothos.1@city.ac.ukhttp://www.staff.city.ac.uk/~sbbh932/
Jerome R. Busemeyer
Affiliation:
Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405. jbusemey@indiana.eduhttp://mypage.iu.edu/~jbusemey/home.html
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Abstract

Classical (Bayesian) probability (CP) theory has led to an influential research tradition for modeling cognitive processes. Cognitive scientists have been trained to work with CP principles for so long that it is hard even to imagine alternative ways to formalize probabilities. However, in physics, quantum probability (QP) theory has been the dominant probabilistic approach for nearly 100 years. Could QP theory provide us with any advantages in cognitive modeling as well? Note first that both CP and QP theory share the fundamental assumption that it is possible to model cognition on the basis of formal, probabilistic principles. But why consider a QP approach? The answers are that (1) there are many well-established empirical findings (e.g., from the influential Tversky, Kahneman research tradition) that are hard to reconcile with CP principles; and (2) these same findings have natural and straightforward explanations with quantum principles. In QP theory, probabilistic assessment is often strongly context- and order-dependent, individual states can be superposition states (that are impossible to associate with specific values), and composite systems can be entangled (they cannot be decomposed into their subsystems). All these characteristics appear perplexing from a classical perspective. However, our thesis is that they provide a more accurate and powerful account of certain cognitive processes. We first introduce QP theory and illustrate its application with psychological examples. We then review empirical findings that motivate the use of quantum theory in cognitive theory, but also discuss ways in which QP and CP theories converge. Finally, we consider the implications of a QP theory approach to cognition for human rationality.

Keywords

category membershipclassical probability theoryconjunction effectdecision makingdisjunction effectinterference effectsjudgmentquantum probability theoryrationalitysimilarity ratings
Type
Target Article
Information
Behavioral and Brain Sciences , Volume 36 , Issue 3 , June 2013 , pp. 255 - 274
Copyright
Copyright © Cambridge University Press 2013 

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