Defining Explanation in Probabilistic Systems

Urszula Chajewska; Joseph Y. Halpern

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arXiv · 1302.1526

Defining Explanation in Probabilistic Systems

Urszula Chajewska·Joseph Y. Halpern

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Abstract

As probabilistic systems gain popularity and are coming into wider use, the need for a mechanism that explains the system's findings and recommendations becomes more critical. The system will also need a mechanism for ordering competing explanations. We examine two representative approaches to explanation in the literature - one due to Gärdenfors and one due to Pearl - and show that both suffer from significant problems. We propose an approach to defining a notion of "better explanation" that combines some of the features of both together with more recent work by Pearl and others on causality.

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Urszula Chajewska, Joseph Y. Halpern. 2013-02-06. Defining Explanation in Probabilistic Systems. https://arxiv.org/abs/1302.1526

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