Information Aggregation as one of the Pillars of Intelligent Systems

In intelligent systems where fuzzy rule base and reasoning mechanism are applied, like fuzzy control systems, decision support and expert systems, one of the key issues is the problem of aggregation of information represented by membership functions. Since the pioneering work of Prof. Lotfi Zadeh [21] a great number of fuzzy connectives, aggregation operators have been introduced. The results of continuous research in this area have proved that the generally used t-norms, t-conorms do not follow always the real phenomena and do not provide optimal performance. The requirement to develop more sophisticated intelligent systems demands to find new operator families. This paper summarizes some new approaches to information aggregation from the literature and the research results of the authors and his colleagues that have been carried out in recent years on generalization of conventional operators. Key–Words: t-norm, t-conorm, uninorm, entropyand distance-based conjunctions and disjunctions