Building on solid foundations: from conceptual semantics to intelligent-systems applications

Summary form only given. In the past, we have endeavored to develop a better understanding of the nature of fuzzy-logic approaches on the basis of their relation to other fundamental scientific notions. While many of these efforts evolved in the context of specific applications, their ultimate motivation was the enhancement of basic understanding-particularly in the area of the relations between various approximate-reasoning methodologies. In this presentation we review applied methods stemming from these foundations-relating fuzzy-logic concepts to notions of utility, cost, and similarity-emphasizing the need for the understanding of basic conceptual structures in the development of effective approaches to treat a wide variety of problems. We will review recent applications of approaches based on this view of fuzzy logic to three major Intelligent-system development problems: distributed robotics, qualitative description of complex objects, and knowledge discovery and retrieval in very large databases. We will present major technical issues arising in the consideration of these problems while addressing also fundamental questions of essential importance to the development and understanding of applicable approaches. In particular, we will consider matters related to the notions of team and individual goals, negotiation, and agent-based preferences in the context of distributed robotics; the concepts of cluster and clustering in the context of data analysis and understanding; and the relations between knowledge-based structures, such as ontologies and know ledge-bases, and similarity measures in the context of information-retrieval problems.