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What are the appropriate axioms of rationality for reasoning under uncertainty with resource-constrained systems?

Published online by Cambridge University Press:  11 March 2020

Harald Atmanspacher
Collegium Helveticum, Zürich, 8006Switzerlandatmanspacher@collegium.ethz.ch
Irina Basieva
Department of Psychology, City University London, LondonEC1V 0HB, United
Jerome R. Busemeyer
Psychological Brain Sciences, Indiana University, IN47405jbusemey@indiana.edushiffrin@indiana.edu
Andrei Y. Khrennikov
Department of Mathematics at Linnaeus University, Linnaeus University, 351 95Växjö, Sweden. andrei.khrennikov@lnu.se
Emmanuel M. Pothos
Department of Psychology, City University London, LondonEC1V 0HB, United
Richard M. Shiffrin
Psychological Brain Sciences, Indiana University, IN47405jbusemey@indiana.edushiffrin@indiana.edu
Zheng Wang
Department of Communication, The Ohio State University, Columbus, OH43210. wang.1243@osu.edu


When constrained by limited resources, how do we choose axioms of rationality? The target article relies on Bayesian reasoning that encounter serious tractability problems. We propose another axiomatic foundation: quantum probability theory, which provides for less complex and more comprehensive descriptions. More generally, defining rationality in terms of axiomatic systems misses a key issue: rationality must be defined by humans facing vague information.

Open Peer Commentary
Copyright © Cambridge University Press 2020

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