ECAI 2004 Conference Paper

[full paper]

Distributed Reasoning in a Peer to Peer Setting

Philippe Adjiman, Philippe Chatalic, Francois Goasdoue, Marie-Christine Rousset, Laurent Simon

In a peer to peer inference system, each peer can reason locally but can also solicit some of its acquaintances, which are peers sharing part of its vocabulary. In this paper, we consider peer to peer inference systems in which the local theory of each peer is a set of propositional clauses defined upon a local vocabulary. An important characteristic of peer to peer inference systems is that the global theory (the union of all peer theories) is not known (as opposed to partition-based reasoning systems). The contribution of this paper is twofold. We provide the first consequence finding algorithm in a peer to peer setting: it is incremental, anytime and computes consequences gradually from the solicited peer to peers that are more and more distant. We exhibit a sufficient condition on the acquaintance graph of the peer to peer inference system for guaranteeing the completeness of this algorithm.

Keywords: Automated Reasoning, Deduction, Consequence Finding, Distributed AI, Knowledge-Based Systems, Knowledge Representation

Citation: Philippe Adjiman, Philippe Chatalic, Francois Goasdoue, Marie-Christine Rousset, Laurent Simon: Distributed Reasoning in a Peer to Peer Setting. In R.López de Mántaras and L.Saitta (eds.): ECAI2004, Proceedings of the 16th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2004, pp.945-946.