Bayes, Bounds, and Rational Analysis
Philosophy of Science2017Vol. 85(1), pp. 79–101
Citations Over TimeTop 1% of 2017 papers
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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