TY - BOOK AU - Kaburlasos,Vassilis G. ED - SpringerLink (Online service) TI - Towards a Unified Modeling and Knowledge-Representation based on Lattice Theory: Computational Intelligence and Soft Computing Applications SN - 9783540341703 AV - TA329-348 U1 - 519 23 PY - 2006/// CY - Berlin, Heidelberg PB - Springer Berlin Heidelberg KW - Engineering KW - Artificial intelligence KW - Mathematics KW - Engineering mathematics KW - Appl.Mathematics/Computational Methods of Engineering KW - Artificial Intelligence (incl. Robotics) KW - Applications of Mathematics N1 - The Context -- Origins in Context -- Relevant Literature Review -- Theory and Algorithms -- Novel Mathematical Background -- Real-World Grounding -- Knowledge Representation -- The Modeling Problem and its Formulation -- Algorithms for Clustering, Classification, and Regression -- Applications and Comparisons -- Numeric Data Applications -- Nonnumeric Data Applications -- Connections with Established Paradigms -- Conclusion -- Implementation Issues -- Discussion N2 - By ‘model’ we mean a mathematical description of a world aspect. With the proliferation of computers a variety of modeling paradigms emerged under computational intelligence and soft computing. An advancing technology is currently fragmented due, as well, to the need to cope with different types of data in different application domains. 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 is shown how rigorous analysis and design can be pursued in soft computing using conventional (hard computing) methods. Moreover, non-Turing computation can be pursued. The material here is multi-disciplinary based on our on-going research published in major scientific journals and conferences. Experimental results by various algorithms are demonstrated extensively. Relevant work by other authors is also presented both extensively and comparatively UR - http://dx.doi.org/10.1007/978-3-540-34170-3 ER -