Modeling Decisions for Artificial Intelligence
Vicenç Torra, Yasuo Narukawa, and Sadaaki Miyamoto
This special issue presents seven papers that are revised and expanded versions of papers presented at the 2nd International Conference on “Modeling Decisions for Artificial Intelligence” (MDAI). This conference, that took place in Tsukuba (Japan) in July 2005, was the second of the series of MDAI conferences that were initiated in 2004 in Barcelona (Catalonia, Spain). In April 2006, the third edition was held in Tarragona (Catalonia, Spain) and the fourth one is planned in Kitakyushu (Japan) in August 2007. These series of conferences were initiated to foster the use of decision related tools as well as information fusion technologies within artificial intelligence applications. In this issue, we present enhanced version of seven papers presented in the conference. The first paper describes a tool that uses fuzzy logic and neural networks for assigning a treatment to rheumatism. The selection of the appropriate treatment follows oriental medicine. The second paper by Wanyama and Far describes a tool for trade-off analysis to be used in those situations related with decision making in which there is no dominant solution. The third paper is devoted to autonomous mobile robots. The authors describe a multi-layered fuzzy control system for the self-localization of the robot. Two papers devoted to fuzzy clustering follow in this issue. First, one that presents a regularization approach with nonlinear membership weights. One of the proposed methods makes not only possible to perform attraction of data to clusters but also repulsion between different clusters. The second paper on clustering proposes the simultaneous application of homogeneity analysis and fuzzy clustering through the consideration of an appropriate objective function that includes two types of memberships. The sixth paper presents a tool for e-mail classification. The tool brings the name of FIS-CRM that stands for Fuzzy Interrelations and Synonymy Conceptual Representation Model. The issue finishes with a paper on meta-heuristic algorithms for a class of container loading problems. To finish this introduction, we would like to thank the referees for their work on the review process as well as to thank Prof. Hirota, Editor-in-Chief of this journal, for providing us with the opportunity to edit this special issue. The help of Kazuki Ohmori and Kenta Uchino from Fuji Technology Press Ltd. is also acknowledged.