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Explaining Actual Causation via Reasoning About Actions and Change

Author Emily C. LeBlanc



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Emily C. LeBlanc
  • College of Computing and Informatics, Drexel University, Philadelphia, PA, USA

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Emily C. LeBlanc. Explaining Actual Causation via Reasoning About Actions and Change. In Technical Communications of the 34th International Conference on Logic Programming (ICLP 2018). Open Access Series in Informatics (OASIcs), Volume 64, pp. 16:1-16:11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/OASIcs.ICLP.2018.16

Abstract

In causality, an actual cause is often defined as an event responsible for bringing about a given outcome in a scenario. In practice, however, identifying this event alone is not always sufficient to provide a satisfactory explanation of how the outcome came to be. In this paper, we motivate this claim using well-known examples and present a novel framework for reasoning more deeply about actual causation. The framework reasons over a scenario and domain knowledge to identify additional events that helped to "set the stage" for the outcome. By leveraging techniques from Reasoning about Actions and Change, the approach supports reasoning over domains in which the evolution of the state of the world over time plays a critical role and enables one to identify and explain the circumstances that led to an outcome of interest. We utilize action language AL for defining the constructs of the framework. This language lends itself quite naturally to an automated translation to Answer Set Programming, using which, reasoning tasks of considerable complexity can be specified and executed. We speculate that a similar approach can also lead to the development of algorithms for our framework.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Knowledge representation and reasoning
  • Computing methodologies → Causal reasoning and diagnostics
  • Computing methodologies → Temporal reasoning
Keywords
  • Actual Cause
  • Explanation
  • Reasoning about Actions and Change
  • Action Language
  • Answer Set Programming
  • Knowledge Representation and Reasoning

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