Probabilistic Argumentation Systems and Abduction

Authors:
J. Kohlas;D. Berzati;R. Haenni
Affiliations:
Department of Informatics DIUF, University of Fribourg, CH–1700 Fribourg, Switzerland E-mail: juerg.kohlas@unifr.ch;Department of Informatics DIUF, University of Fribourg, CH–1700 Fribourg, Switzerland;Department of Informatics DIUF, University of Fribourg, CH–1700 Fribourg, Switzerland
Venue:
Annals of Mathematics and Artificial Intelligence
Year:
2002

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Abstract

Probabilistic argumentation systems are based on assumption-based reasoning for obtaining arguments supporting hypotheses and on probability theory to compute probabilities of supports. Assumption-based reasoning is closely related to hypothetical reasoning or inference through theory formation. The latter approach has well known relations to abduction and default reasoning. In this paper assumption-based reasoning, as an alternative to theory formation aiming at a different goal, will be presented and its use for abduction and model-based diagnostics will be explained. Assumption-based reasoning is well suited for defining a probability structure on top of it. On the base of the relationships between assumption-based reasoning on the one hand and abduction on the other hand, the added value introduced by probability into model based diagnostics will be discussed. Furthermore, the concepts of complete and partial models are introduced with the goal to study the quality of inference procedures. In particular this will be used to compare abductive to possible explanations.