Inference to the Best Explanation versus Bayes’s Rule in a Social Setting

Igor Douven
Centre National de la Recherche Scientifique
This article compares inference to the best explanation with Bayes’s rule in a social setting, specifically, in the context of a variant of the Hegselmann–Krause model in which agents not only update their belief states on the basis of evidence they receive directly from the world, but also take into account the belief states of their fellow agents. So far, the update rules mentioned have been studied only in an individualistic setting, and it is known that in such a setting both have their strengths as well as their weaknesses. It is shown here that in a social setting, inference to the best explanation outperforms Bayes’s rule according to every desirable criterion. 1 What Is Inference to the Best Explanation?2 Judging the Rules—By Which Lights?3 From an Individualistic to a Social Perspective 3.1 The Hegselmann–Krause model 3.2 A probabilistic extension of the Hegselmann–Krause model 3.3 Simulations4 Results and Discussion5 Interpretation6 Conclusion.
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Reprint years 2015, 2017
DOI 10.1093/bjps/axv025
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References found in this work BETA

A Nonpragmatic Vindication of Probabilism.James M. Joyce - 1998 - Philosophy of Science 65 (4):575-603.
The Inference to the Best Explanation.Gilbert H. Harman - 1965 - Philosophical Review 74 (1):88-95.

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Citations of this work BETA

Abduction.Igor Douven - 2011 - Stanford Encyclopedia of Philosophy.
Inference to the Best Explanation Made Incoherent.Nevin Climenhaga - 2017 - Journal of Philosophy 114 (5):251-273.
Is Explanatoriness a Guide to Confirmation? A Reply to Climenhaga.William Roche & Elliott Sober - 2017 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 48 (4):581-590.

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