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Embracing Background Knowledge in the Analysis of Actual Causality: An Answer Set Programming Approach
Published online by Cambridge University Press: 26 July 2023
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.
- Type
- Original Article
- Information
- Theory and Practice of Logic Programming , Volume 23 , Issue 4: 2023 International Conference on Logic Programming , July 2023 , pp. 715 - 729
- Copyright
- © The Author(s), 2023. Published by Cambridge University Press