Coherence, Explanation, and Hypothesis Selection

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This paper provides a new approach to inference to the best explanation (IBE) based on a new coherence measure for comparing how well hypotheses explain the evidence. It addresses a number of criticisms of the use of probabilistic measures in this context by Clark Glymour ([2015]), including limitations of earlier work on IBE (Glass [2012]). Computer experiments are used to show that the new approach finds the truth with a high degree of accuracy in hypothesis selection tasks and that in some cases its accuracy is greater than hypothesis selection based on maximizing posterior probability. Hence, by overcoming some of the problems with the previous approach, this work provides a more adequate defence of IBE and suggests that IBE not only tracks truth but also has practical advantages over the previous approach. Applications of the new approach to parameter estimation and model selection are also explored.
Original languageEnglish
Pages (from-to)1-29
Number of pages29
JournalBritish Journal for the Philosophy of Science
Early online date28 Aug 2018
Publication statusPublished (in print/issue) - 28 Nov 2020


  • coherence
  • explanatory power
  • inference to the best explanation
  • Bayesian inference
  • computer simulation
  • model selection
  • History and Philosophy of Science
  • History
  • Philosophy


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