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

In 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.

• Type: Conference
• Year: 2006
• Where: ECAI
• Authors: Philippe Chatalic, Gia Hien Nguyen, Marie-Christine Rousset
• Keywords: Artificial Intelligence, Collective Reasoning Task, ECAI 2006, Peer Theories Model, Peer-to-peer Inference System