A Revision-Based Approach to Resolving Conflicting Information
This is an incremental improvement for AI systems dealing with knowledge representation and reasoning, specifically in conflict resolution.
The paper tackles the problem of resolving conflicting information by proposing a revision-based approach that generalizes the Disjunctive Maxi-Adjustment (DMA) method, showing that both versions are computationally easier than DMA.
In this paper, we propose a revision-based approach for conflict resolution by generalizing the Disjunctive Maxi-Adjustment (DMA) approach (Benferhat et al. 2004). Revision operators can be classified into two different families: the model-based ones and the formula-based ones. So the revision-based approach has two different versions according to which family of revision operators is chosen. Two particular revision operators are considered, one is the Dalal's revision operator, which is a model-based revision operator, and the other is the cardinality-maximal based revision operator, which is a formulabased revision operator. When the Dalal's revision operator is chosen, the revision-based approach is independent of the syntactic form in each stratum and it captures some notion of minimal change. When the cardinalitymaximal based revision operator is chosen, the revision-based approach is equivalent to the DMA approach. We also show that both approaches are computationally easier than the DMA approach.