Incorporation of a priori knowledge, such as expert knowledge, meta-heuristics and human preferences, as well as domain knowledge acquired during evolu tionary search, into evolutionary algorithms has received increasing interest in the recent years. It has been shown from various motivations that knowl edge incorporation into evolutionary search is able to significantly improve search efficiency. However, results on knowledge incorporation in evolution ary computation have been scattered in a wide range of research areas and a systematic handling of this important topic in evolutionary computation still lacks. This edited book is a first attempt to put together the state-of-art and re cent advances on knowledge incorporation in evolutionary computation within a unified framework. Existing methods for knowledge incorporation are di vided into the following five categories according to the functionality of the incorporated knowledge in the evolutionary algorithms. 1. Knowledge incorporation in representation, population initialization, - combination and mutation. 2. Knowledge incorporation in selection and reproduction. 3. Knowledge incorporation in fitness evaluations. 4. Knowledge incorporation through life-time learning and human-computer interactions. 5. Incorporation of human preferences in multi-objective evolutionary com putation. The intended readers of this book are graduate students, researchers and practitioners in all fields of science and engineering who are interested in evolutionary computation. The book is divided into six parts. Part I contains one introductory chapter titled "A selected introduction to evolutionary computation" by Yao, which presents a concise but insightful introduction to evolutionary computation.
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This carefully edited book puts together the state-of-the-art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self-contained view of knowledge incorporation in evolutionary computation including a concise introduction to evolutionary algorithms as well as knowledge representation methods. "Knowledge Incorporation in Evolutionary Computation" is a valuable reference for researchers, students and professionals from engineering and computer science, in particular in the areas of artificial intelligence, soft computing, natural computing, and evolutionary computation.
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Seller: Universitätsbuchhandlung Herta Hold GmbH, Berlin, Germany
2005. 16 x 24 cm. XIII, 548 S. XIII, 548 p. Hardcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. (Studies in Fuzziness and Soft Computing). Sprache: Englisch. Seller Inventory # 252ZB
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Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. State of the art in knowledge incorporation in evolutionary computation Comprehensive and self-contained Includes a concise introduction to evolutionary algorithms as well as knowledge representation methodsIncorporation of a priori. Seller Inventory # 4885683
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Incorporation of a priori knowledge, such as expert knowledge, meta-heuristics and human preferences, as well as domain knowledge acquired during evolu tionary search, into evolutionary algorithms has received increasing interest in the recent years. It has been shown from various motivations that knowl edge incorporation into evolutionary search is able to significantly improve search efficiency. However, results on knowledge incorporation in evolution ary computation have been scattered in a wide range of research areas and a systematic handling of this important topic in evolutionary computation still lacks. This edited book is a first attempt to put together the state-of-art and re cent advances on knowledge incorporation in evolutionary computation within a unified framework. Existing methods for knowledge incorporation are di vided into the following five categories according to the functionality of the incorporated knowledge in the evolutionary algorithms. 1. Knowledge incorporation in representation, population initialization, - combination and mutation. 2. Knowledge incorporation in selection and reproduction. 3. Knowledge incorporation in fitness evaluations. 4. Knowledge incorporation through life-time learning and human-computer interactions. 5. Incorporation of human preferences in multi-objective evolutionary com putation. The intended readers of this book are graduate students, researchers and practitioners in all fields of science and engineering who are interested in evolutionary computation. The book is divided into six parts. Part I contains one introductory chapter titled 'A selected introduction to evolutionary computation' by Yao, which presents a concise but insightful introduction to evolutionary computation. 564 pp. Englisch. Seller Inventory # 9783540229025
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Buch. Condition: Neu. Knowledge Incorporation in Evolutionary Computation | Yaochu Jin | Buch | xiii | Englisch | 2004 | Springer-Verlag GmbH | EAN 9783540229025 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. Seller Inventory # 102437272
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