Paper ID: 2306.03874 • Published Jun 6, 2023
Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach
Michael Gelfond, Jorge Fandinno, Evgenii Balai
TL;DR
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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.