Configurations for inference from causal statements: preliminary report

  • Authors:
  • Philippe Besnard;Marie-Odile Cordier;Yves Moinard

  • Affiliations:
  • IRISA, Rennes, France;IRISA, Rennes, France;IRISA, Rennes, France

  • Venue:
  • AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
  • Year:
  • 2005

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Abstract

Our aim is to provide a rigorous logical framework for describing causal relations (involved in reasoning tasks such as diagnosis). We propose a framework which is minimal in that only a few properties, hopefully uncontroversial, are imposed upon it. Our semantics of a causal relation is based on collections of possible cases, called “configurations”. We mention several features which causation makes undesirable despite commonly held beliefs. We show how our logic avoid such pitfalls and generally conforms with a strict view of causation.