Multiagent Approach to Fuzzy-Linguistic Knowledge Integration

Abstract

The paper aims to give at least a partial answer to an urgent need for knowledge processing systems equipped with semantic capabilities. One of the crucial goals is to reflect inner computational models and numerical data outside of the system by presenting linguistic statements easily understood by a non-expert user. The paper follows a motivational scenario and presents a layered approach to knowledge integration. The fundamental rationale behind the proposed approach is that a degree of inconsistency of the whole body of knowledge should be incorporated into the formed summary and conveyed to the external user of the system. The paper deals with a practically important problem of processing modal epistemic statements about an object exhibiting some set of fuzzy properties. The statements represent distributed knowledge of some agent population and are represented on the level of a semi-natural language. In particular, the paper describes an approach to two-level fuzzy-linguistic knowledge integration based on the consensus-theory and clustering methods. In particular, it discusses the difference between the in-cluster level and the cross-cluster level. While this paper considers an environment limited to a single object with multiple properties, it is directly extendable to environments with multiple objects. The reduction is purely technical as it allows for a simplification of a notation and presented descriptions.