Information and Explanatory Goodness

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Abstract

I propose a qualitative Bayesian account of explanatory goodness that is analogous to the Bayesian account of incremental confirmation. This is achieved by means of a complexity criterion according to which an explanation h is good if the reduction in the complexity of the explanandum e brought about by h (the explanatory gain) is greater than the additional complexity introduced by h in the context of e (the explanatory cost). To illustrate the account, I apply it in the context of ad hoc hypotheses.
Original languageEnglish
Pages (from-to)1-14
Number of pages14
JournalErkenntnis
Early online date20 Apr 2023
DOIs
Publication statusPublished online - 20 Apr 2023

Bibliographical note

Funding Information:
I would like to thank participants at the Conference on Scientific Explanations, Competing and Conjunctive at the University of Utah in June, 2019 for helpful discussions and Jonah Schupbach and Tomoji Shogenji for detailed feedback on earlier drafts. I would also like to thank anonymous reviewers for very helpful comments. This publication was made possible through the support of a grant from the John Templeton Foundation (Grant no. 61115). The opinions expressed in this publication are those of the authors and do not necessarily reflect the views of the John Templeton Foundation.

Publisher Copyright:
© 2023, The Author(s).

Keywords

  • Explanation
  • Explanatory goodness
  • Explanatory power
  • ad hoc hypotheses
  • Bayesian approach
  • Confirmation

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