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

Author:

Michael Gelfond, Jorge Fandinno, Evgenii Balai

Keyword:

Computer Science, Artificial Intelligence, Artificial Intelligence (cs.AI), Logic in Computer Science (cs.LO)

journal:

date:

2023-06-05 16:00:00

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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