Reasoning with Inconsistencies in Propositional Peer-to-Peer Inference Systems
Abstract
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.
Domains
Artificial Intelligence [cs.AI]
Origin : Files produced by the author(s)
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