Journal Article

Inductive Influence

Jon Williamson

in The British Journal for the Philosophy of Science

Published on behalf of British Society for the Philosophy of Science

Volume 58, issue 4, pages 689-708
Published in print December 2007 | ISSN: 0007-0882
Published online September 2007 | e-ISSN: 1464-3537 | DOI: http://dx.doi.org/10.1093/bjps/axm032
Inductive Influence

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Objective Bayesianism has been criticised for not allowing learning from experience: it is claimed that an agent must give degree of belief [math] 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. 1

Introduction

2

The Problem

3

Diagnosis

4

Objective Bayesian Nets

5

Resolution

6

The Johnson–Carnap Continuum

7

The Nix–Paris Continuum

8

Linguistic Slack

9

Frequencies and Degrees of Belief

10

Conclusion

Journal Article.  6855 words.  Illustrated.

Subjects: Philosophy of Science ; Science and Mathematics

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