Combining multiple knowledge bases by negotiation: a possibilistic approach

Authors:
Guilin Qi;Weiru Liu;David A. Bell
Affiliations:
School of Computer Science, Queen's University Belfast, Belfast, UK;School of Computer Science, Queen's University Belfast, Belfast, UK;School of Computer Science, Queen's University Belfast, Belfast, UK
Venue:
ECSQARU'05 Proceedings of the 8th European conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Year:
2005

Citing 5
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Abstract

A negotiation model consists of two functions: a negotiation function and a weakening function. A negotiation function is defined to choose the weakest sources and these sources will weaken their point of view using a weakening function. However, the currently available belief negotiation models are based on classical logic, which make it difficult to define weakening functions. In this paper, we define a prioritized belief negotiation model in the framework of possibilistic logic. The priority between formulae provides us with important information to decide which beliefs should be discarded. The problem of merging uncertain information from different sources is then solved by two steps. First, beliefs in the original knowledge bases will be weakened to resolve inconsistencies among them. This step is based on a prioritized belief negotiation model. Second, the knowledge bases obtained by the first step are combined using a conjunctive operator or a reinforcement operator in possbilistic logic.