Journal Article

Explanationist Aid for the Theory of Inductive Logic

Michael Huemer

in The British Journal for the Philosophy of Science

Published on behalf of British Society for the Philosophy of Science

Volume 60, issue 2, pages 345-375
Published in print June 2009 | ISSN: 0007-0882
Published online March 2009 | e-ISSN: 1464-3537 | DOI: http://dx.doi.org/10.1093/bjps/axp008
Explanationist Aid for the Theory of Inductive Logic

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A central problem facing a probabilistic approach to the problem of induction is the difficulty of sufficiently constraining prior probabilities so as to yield the conclusion that induction is cogent. The Principle of Indifference, according to which alternatives are equiprobable when one has no grounds for preferring one over another, represents one way of addressing this problem; however, the Principle faces the well-known problem that multiple interpretations of it are possible, leading to incompatible conclusions. I propose a partial solution to the latter problem, drawing on the notion of explanatory priority. The resulting synthesis of Bayesian and inference-to-best-explanation approaches affords a principled defense of prior probability distributions that support induction.

A Probabilistic Formulation of the Problem of Induction

A Problem with Objective Bayesianism 2.1

Intuitive motivation for the Principle of Indifference

2.2

The inconsistency objection

2.3

An effort to contain the problem

Explanationist Relief for Objective Bayesianism 3.1

Explanation and explanatory priority

3.2

Explanatory priority and the assignment of priors

3.3

In defense of Laplace

3.4

The metaphysics of the explanationist defense: causation and laws

3.5

Inference to the best explanation?

Problems and objections 4.1

Unknown explanatory possibilities

4.2

Empirical reasoning about explanatory priority

4.3

The probability of deterministic laws

4.4

Changing chances

4.5

Scruples concerning a priori probability

Journal Article.  13339 words.  Illustrated.

Subjects: Philosophy of Science ; Science and Mathematics

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