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

• URL: http://arxiv.org/abs/2306.03874v1
• Date: Tue, 6 Jun 2023 17:21:21 GMT
• Title: Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach
• Authors: Michael Gelfond, Jorge Fandinno and Evgenii Balai
• Abstract summary: This paper presents a rich knowledge representation language aimed at formalizing causal knowledge. A definition of cause is presented and used to analyze the actual causes of changes with respect to sequences of actions representing those examples.
• Score: 6.685412769221564
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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