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Artificial explanations: the epistemological interpretation of explanation in AI

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Abstract

In this paper I critically examine the notion of explanation used in artificial intelligence in general, and in the theory of belief revision in particular. I focus on two of the best known accounts in the literature: Pagnucco’s abductive expansion functions and Gärdenfors’ counterfactual analysis. I argue that both accounts are at odds with the way in which this notion has historically been understood in philosophy. They are also at odds with the explanatory strategies used in actual scientific practice. At the end of the paper I outline a set of desiderata for an epistemologically motivated, scientifically informed belief revision model for explanation.

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  1. Universidad de los Andes, Bogota, Colombia

    Andrés Páez

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  1. Andrés Páez
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Páez, A. Artificial explanations: the epistemological interpretation of explanation in AI. Synthese 170, 131–146 (2009). https://doi.org/10.1007/s11229-008-9361-3

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