Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach
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Abstract (arXiv)
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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References · 5
- 2015A Modification of the Halpern-Pearl Definition of Causalitycited by 47
- 2020A System for Explainable Answer Set Programmingcited by 10
- 2020The Counterfactual NESS Definition of Causationcited by 8
- 2013Causes and Explanations: A Structural-Model Approach --- Part 1: Causescited by 6
- 2016Enablers and Inhibitors in Causal Justifications of Logic Programscited by 2
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