Behavioral and Brain Sciences

Authors' Response

The uncertain reasoner: Bayes, logic, and rationality

Mike Oaksforda1 and Nick Chatera2

a1 School of Psychology, Birkbeck College London, London, WC1E 7HX, United Kingdom

a2 Division of Psychology and Language Sciences & ESRC Centre for Economic Learning and Social Evolution, University College London, London, WC1E 6BT, United Kingdom.


Human cognition requires coping with a complex and uncertain world. This suggests that dealing with uncertainty may be the central challenge for human reasoning. In Bayesian Rationality we argue that probability theory, the calculus of uncertainty, is the right framework in which to understand everyday reasoning. We also argue that probability theory explains behavior, even on experimental tasks that have been designed to probe people's logical reasoning abilities. Most commentators agree on the centrality of uncertainty; some suggest that there is a residual role for logic in understanding reasoning; and others put forward alternative formalisms for uncertain reasoning, or raise specific technical, methodological, or empirical challenges. In responding to these points, we aim to clarify the scope and limits of probability and logic in cognitive science; explore the meaning of the “rational” explanation of cognition; and re-evaluate the empirical case for Bayesian rationality.

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