A Stratification of Possibilistic Partial Explanations

Several problems are connected, in the literature, to causality: prediction, explanation, action, planning and natural language processing… In a recent paper, Halpern and Pearl introduced an elegant definition of causal (partial) explanation in the structural-model approach, which is based on their notions of weak and actual cause [5]. Our purpose in this paper is to partially modify this definition, rather than to use a probability (quantitative modelisation) we suggest to affect a degree of possibility (a more qualitative modelisation) which is nearer to the human way of reasoning, by using the possibilistic logic. A stratification of all possible partial explanations will be given to the agent for a given request, the explanations in the first strate are more possible than those belonging to the other strates. We compute the complexity of this strafication.

Authors and Affiliations

1. Institut d’Informatique, USTHB, EL Alia, Alger, BP 32, Algeria

   Sara Boutouhami & Aicha Mokhtari

Editors and Affiliations

1. AI Group Department of Engineering Mathematics, University of Bristol, BS8 1TR, Bristol, UK

   Jonathan Lawry

2. Statistics and Operations Research, Rey Juan Carlos University, C-Tulip˙n s/n MÛstoles28933, Spain

   Enrique Miranda

3. Intelligent Systems Group Department of Electronics & Computer Science, University of Santiago de Compostela Santiago de Compostela, Spain

   Alberto Bugarin

4. Department of Applied Mathematics, Beijing University of Technology, 100022, Beijing, P.R. China

   Shoumei Li

5. Dpto. Estadistica e I.O y D.M. Calle Calvo Sotelo s/n, Universiad de Oviedo Fac. Ciencias, 33071, Oviedo, Spain

   Maria Angeles Gil

6. Systems Research Institute Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

   Przemys aw Grzegorzewski

7. Systems Research Institute Polish Academy of Sciences, Newelska 6, 01-447, Warsaw, Poland

   Olgierd Hyrniewicz

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