Deriving explanations from causal information

Philippe Besnard 1 Marie-Odile Cordier 1 Yves Moinard 1
1 DREAM - Diagnosing, Recommending Actions and Modelling
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : We define an inference system to capture explanations based on causal statements, using an ontology in the form of an $IS$-$A$ hierarchy. We introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of formal inference patterns from causal statements to explanation statements. We introduce an elementary ontology which gives greater expressiveness to the system while staying close to propositional reasoning. We provide an inference system that captures the patterns discussed, in a datalog (limited predicate) framework.
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https://hal.inria.fr/inria-00462972
Contributor : René Quiniou <>
Submitted on : Wednesday, March 10, 2010 - 4:49:32 PM
Last modification on : Thursday, November 15, 2018 - 11:57:04 AM

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  • HAL Id : inria-00462972, version 1

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Philippe Besnard, Marie-Odile Cordier, Yves Moinard. Deriving explanations from causal information. ECAI 2008 (18th European Conference on Artificial Intelligence), 2008, Patras, Greece. pp.723--724. ⟨inria-00462972⟩

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