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Titlebook: Discrete Event Modeling and Simulation Technologies; A Tapestry of System Hessam S. Sarjoughian,Fran?ois E. Cellier Book 2001 Springer Scie

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書目名稱Discrete Event Modeling and Simulation Technologies
副標題A Tapestry of System
編輯Hessam S. Sarjoughian,Fran?ois E. Cellier
視頻videohttp://file.papertrans.cn/282/281096/281096.mp4
圖書封面Titlebook: Discrete Event Modeling and Simulation Technologies; A Tapestry of System Hessam S. Sarjoughian,Fran?ois E. Cellier Book 2001 Springer Scie
描述The initial ideas behind this edited volume started in spring of 1998 - some two years before the sixtieth birthday of Bernard P. Zeigler. The idea was to bring together distinguished researchers, colleagues, and former students of Professor Zeigler to present their latest findings at the AIS‘ 2000 conference. During the spring of 1999, the initial ideas evolved into creating a volume of articles surrounding seminal concepts pertaining to modeling and simulation as proposed, developed, and advocated by Professor Zeigler throughout his scientific career. Also included would be articles describing progress covering related aspects of software engineering and artificial intelligence. As this volume is emphasizing concepts and ideas spawned by the work of Bernard P. Zeigler, it is most appropriate to offer a biographical sketch of his scientific life, thus putting into a historical perspective the contributions presented in this volume as well as new research directions that may lie ahead! Bernard P. Zeigler was born March 5, 1940, in Montreal, Quebec, Canada, where he obtained his bachelor‘s degree in engineering physics in 1962 from McGill University. Two years later, having complete
出版日期Book 2001
關鍵詞agent-based model; agent-based modeling; artificial intelligence; development; intelligence; learning; mod
版次1
doihttps://doi.org/10.1007/978-1-4757-3554-3
isbn_softcover978-1-4419-2868-9
isbn_ebook978-1-4757-3554-3
copyrightSpringer Science+Business Media New York 2001
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The Role of Uncertainty in Systems Modeling,. In GIT, information is defined in terms of relevant uncertainty reduction. Main results regarding measures of uncertainty and uncertainty-based information in Dempster-Shafer theory of evidence and in generalized possibility theory are overviewed, and their role in three basic uncertainty principl
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