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Titlebook: Evolutionary Computing; AISB Workshop, Leeds Terence C. Fogarty Conference proceedings 1994 Springer-Verlag Berlin Heidelberg 1994 algorith

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書目名稱Evolutionary Computing
副標題AISB Workshop, Leeds
編輯Terence C. Fogarty
視頻videohttp://file.papertrans.cn/318/317908/317908.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Evolutionary Computing; AISB Workshop, Leeds Terence C. Fogarty Conference proceedings 1994 Springer-Verlag Berlin Heidelberg 1994 algorith
描述This volume is based on the Workshop on Evolutionary Computing held in Leeds, U.K. in April 1994 under the sponsorship of the Society for the Study of Artificial Intelligence and Simulation of Behaviour. In addition to the 22 best papers presented at the workshop, there are two invited contributions by Ray Paton and Colin Reever..The volume addresses several aspects of evolutionary computing, particularly genetic algorithms, and its applications, for example in search, robotics, signal processing, machine learning, and scheduling. The papers are organized in sections on theoretical and biological foundations, techniques, classifier systems, and applications.
出版日期Conference proceedings 1994
關鍵詞algorithm; algorithms; artificial intelligence; evolution; evolutionary computation; genetic algorithm; ge
版次1
doihttps://doi.org/10.1007/3-540-58483-8
isbn_softcover978-3-540-58483-4
isbn_ebook978-3-540-48999-3Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1994
The information of publication is updating

書目名稱Evolutionary Computing影響因子(影響力)




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書目名稱Evolutionary Computing網(wǎng)絡公開度




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書目名稱Evolutionary Computing被引頻次




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書目名稱Evolutionary Computing年度引用




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書目名稱Evolutionary Computing讀者反饋




書目名稱Evolutionary Computing讀者反饋學科排名




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Genetic algorithms and directed adaptation, examples of directed adaptation in nature and the field of optimised search. A model is described based on directed adaptation and the results of experiments, acting at the level of both the population and the individual, are presented.
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https://doi.org/10.1007/978-94-011-7423-7o learn a complete set of rules. A comparison is also made of the performance of the refined system using only selection to learn individual rules with that of the bucket-brigade and other reinforcement algorithms on the same task.
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Co-evolving Co-operative populations of rules in learning control systems,o learn a complete set of rules. A comparison is also made of the performance of the refined system using only selection to learn individual rules with that of the bucket-brigade and other reinforcement algorithms on the same task.
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Conference proceedings 1994 Artificial Intelligence and Simulation of Behaviour. In addition to the 22 best papers presented at the workshop, there are two invited contributions by Ray Paton and Colin Reever..The volume addresses several aspects of evolutionary computing, particularly genetic algorithms, and its applications,
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