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Bayes, Bounds, and Rational Analysis
Published online by Cambridge University Press: 01 January 2022
Abstract
While Bayesian models have been applied to an impressive range of cognitive phenomena, methodological challenges have been leveled concerning their role in the program of rational analysis. The focus of the current article is on computational impediments to probabilistic inference and related puzzles about empirical confirmation of these models. The proposal is to rethink the role of Bayesian methods in rational analysis, to adopt an independently motivated notion of rationality appropriate for computationally bounded agents, and to explore broad conditions under which (approximately) Bayesian agents would be rational. The proposal is illustrated with a characterization of costs inspired by thermodynamics.
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- Copyright © The Philosophy of Science Association
Footnotes
This article grew out of a presentation to the Bay Bayesians meeting at the University of California, Berkeley, in February 2012, and I would like to thank everyone present there for a very helpful and formative discussion. Thanks also to David Danks, Pedro Ortega, Rob Long, and Richard Samuels for helpful conversations and comments on the article.
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