This eighteen-chapter book presents the latest applications of lattice theory in Computational Intelligence (CI). The book focuses on neural computation, mathematical morphology, machine learning, and (fuzzy) inference/logic. The book comes out of a special session held during the World Council for Curriculum and Instruction World Conference (WCCI 2006). The articles presented here demonstrate how lattice theory may suggest viable alternatives in practical clustering, classification, pattern analysis, and regression applications.

This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It presents novel tools and useful perspectives for effective pattern classification. The material is multi-disciplinary based on on-going research published in major scientific journals and conferences.

This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It presents novel tools and useful perspectives for effective pattern classification. The material is multi-disciplinary based on on-going research published in major scientific journals and conferences.