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arXiv · 2306.03874

Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach

Michael Gelfond·Jorge Fandinno·Evgenii Balai
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Abstract

This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. This language is used for accurately and directly formalizing common benchmark examples from the literature of actual causality. A definition of cause is presented and used to analyze the actual causes of changes with respect to sequences of actions representing those examples.

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Michael Gelfond, Jorge Fandinno, Evgenii Balai. 2023-06-06. Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach. https://arxiv.org/abs/2306.03874

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