This volume contains papers presented at the 6th International Conference on ModelingDecisionsforArti?cialIntelligence(MDAI2009),heldinAwajiIsland, Japan, November 30 - December 2, 2009. This conference followed MDAI 2004 (Barcelona, Catalonia), MDAI 2005 (Tsukuba, Japan), MDAI 2006 (Tarragona, Catalonia), MDAI 2007 (Kitakyushu, Japan), and MDAI 2008 (Sabadell, C- alonia) with proceedings also published in the LNAI series (Vols. 3131, 3558, 3885, 4617, and 5285). The aim of this conference was to provide a forum for researchers to d- cuss the theory and tools for modeling decisions, as well as applications that encompass decision-making processes and information-fusion techniques. The organizers received 61 papers from 15 di?erent countries, from Asia, Europe,andAmerica,28ofwhicharepublishedinthis volume.Eachsubmission received at least two reviews from the Program Committee and a few external reviewers. We would like to express our gratitude to them for their work. The plenary talks presented at the conference are also included in this volume. The conference was supported by the Commemorative Organization for The JapanWorldExposition'70,the TsutomuNakauchiFoundation,HyogoInter- tional Association, the Institute of Systems, Control and Information Engineers (ISCIE),the OperationsResearchSocietyofJapan(ORSJ),the UNESCO Chair in Data Privacy, the Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT), the Catalan Association for Arti?cial Intelligence (ACIA), the Eu- pean Society for Fuzzy Logic and Technology (EUSFLAT), and the Spanish MEC (ARES - CONSOLIDER INGENIO 2010 CSD2007-00004).
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This book constitutes the proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2009, held on Awaji Island, Japan, in November/December 2009.
The 28 papers presented in this book together with 5 invited talks were carefully reviewed and selected from 61 submissions. The topics covered are aggregation operators, fuzzy measures and game theory; decision making; clustering and similarity; computational intelligence and optimization; and machine learning.
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