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The uncertain reasoner: Bayes, logic, and rationality

Oaksford, M; Chater, N; (2009) The uncertain reasoner: Bayes, logic, and rationality. BEHAV BRAIN SCI , 32 (1) 105 - 120. 10.1017/S0140525X0900051X. Green open access

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Abstract

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.

Type: Article
Title: The uncertain reasoner: Bayes, logic, and rationality
Open access status: An open access version is available from UCL Discovery
DOI: 10.1017/S0140525X0900051X
Publisher version: http://dx.doi.org/10.1017/S0140525X0900051X
Language: English
Additional information: © 2009 Cambridge University Press
Keywords: SELECTION TASK, INDIVIDUAL-DIFFERENCES, INFORMATION GAIN, CAUSAL INDUCTION, PROBABILITIES, CONDITIONALS, DECISION, MODELS, INFERENCE, REPRESENTATION
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
URI: https://discovery.ucl.ac.uk/id/eprint/124392
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