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

2023/06/06 by Gelfond, Michael, Fandinno, Jorge, Balai, Evgenii
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Logic in Computer Science (cs.LO)

paper · doi:10.48550/arxiv.2306.03874

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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