Ontology-based inference for causal explanation

Philippe Besnard (1, 2, 3) , Marie-Odile Cordier (1) , Yves Moinard (1)

1 DREAM - Diagnosing, Recommending Actions and Modelling
2 IRIT-LILaC - Logique, Interaction, Langue et Calcul
3 CNRS - Centre National de la Recherche Scientifique

We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first 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, firstly in a purely propositional framework, then in a datalog (limited predicate) framework.

Mots clés: Abduction; Causal reasoning; Explanation

Domaines: Intelligence artificielle [cs.AI]

Philippe Besnard, Marie-Odile Cordier, Yves Moinard. Ontology-based inference for causal explanation. Integrated Computer-Aided Engineering, 2008, 15 (4), pp.351-367. ⟨inria-00476906⟩