Oaksford, Michael and Chater, N. (2009) The uncertain reasoner: Bayes, logic, and rationality. Behavioral and Brain Sciences 32 (1), pp. 105-120. ISSN 0140-525X.Full text not available from this repository.
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.
|School or Research Centre:||Birkbeck Schools and Research Centres > School of Science > Psychological Sciences|
|Date Deposited:||17 Dec 2010 13:45|
|Last Modified:||17 May 2016 15:53|
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