Inductive Influence: Objective Bayesianism has been criticised for not allowing learning from experience: it is claimed that an agent must give degree of belief Formula to the next raven being black, however many other black ravens have been observed. I argue that this objection can be overcome by appealing to objective Bayesian nets, a formalism for representing objective Bayesian degrees of belief. Under this account, previous observations exert an inductive influence on the next observation. I show how this approach can be used to capture the Johnson–Carnap continuum of inductive methods, as well as the Nix–Paris continuum, and show how inductive influence can be measured [Book Review]

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Jon Williamson
University of Kent
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DOI 10.1093/bjps/axm032
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