Reasoning with Inconsistencies in Propositional Peer-to-Peer Inference Systems

Philippe Chatalic; Gia Hien Nguyen; Marie Christine Rousset

inria-00179862, version 1

Reasoning with Inconsistencies in Propositional Peer-to-Peer Inference Systems

Philippe Chatalic ()^a^, 1, 2, Gia Hien Nguyen ()^b^, 1, 3, Marie Christine Rousset^b^, 1, 3

European Conference on Artificial Intelligence (ECAI'06) (2006)

Résumé : n a peer-to-peer inference system, there is no centralized control or hierarchical organization: each peer is equivalent in functionality and cooperates with other peers in order to solve a collective reasoning task. Since peer theories model possibly different viewpoints, even if each local theory is consistent, the global theory may be inconsistent. We exhibit a distributed algorithm detecting inconsistencies in a fully decentralized setting. We provide a fully distributed reasoning algorithm, which computes only well-founded consequences of a formula, i.e., with a consistent set of support.

a – Université Paris Sud - Paris XI
b – Université Joseph Fourier - Grenoble I
1 : GEMO (INRIA Futurs)
INRIA – CNRS : UMR8623 – Université Paris XI - Paris Sud
2 : Laboratoire de Recherche en Informatique (LRI)
CNRS : UMR8623 – Université Paris XI - Paris Sud
3 : Laboratoire d'Informatique de Grenoble (LIG)
Université Joseph Fourier - Grenoble I – Institut Polytechnique de Grenoble - Grenoble Institute of Technology – Université Pierre-Mendès-France - Grenoble II – CNRS : UMR5217

inria-00179862, version 1
http://hal.inria.fr/inria-00179862
oai:hal.inria.fr:inria-00179862
Contributeur : Philippe Chatalic <>
Soumis le : Mardi 16 Octobre 2007, 18:48:11
Dernière modification le : Jeudi 29 Novembre 2012, 11:41:17

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