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Titlebook: Evolutionary Computing; AISB Workshop, Brigh Terence C. Fogarty Conference proceedings 1996 Springer-Verlag Berlin Heidelberg 1996 artifici

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书目名称Evolutionary Computing
副标题AISB Workshop, Brigh
编辑Terence C. Fogarty
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Evolutionary Computing; AISB Workshop, Brigh Terence C. Fogarty Conference proceedings 1996 Springer-Verlag Berlin Heidelberg 1996 artifici
描述This book contains a selection of papers presented at a workshop on evolutionary computing sponsored by the Society for the Study of Artificial Intelligence and Simulation of Behaviour, AISB, at the University of Sussex in Brighton, UK, in April 1996..The 22 revised full papers included in the book, together with one invited contribution, were carefully reviewed by the program committee. Twelve contributions investigate applications of evolutionary computing in various areas, such as learning, scheduling, searching, genetic programming, image processing, and robotics. Eleven papers are devoted to evolutionary computing theory and techniques.
出版日期Conference proceedings 1996
关键词artificial intelligence; evolution; genetic programming; image processing; intelligence; learning; program
版次1
doihttps://doi.org/10.1007/BFb0032768
isbn_softcover978-3-540-61749-5
isbn_ebook978-3-540-70671-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 1996
The information of publication is updating

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The Analogy between Emotions and Judgements,ven area, of arbitrary shape, without contravening the safety distances. The genetic algorithm was able to produce interesting and safe layouts, and merits further investigation for more complicated problems. The genetic algorithm used involved a local hill-climbing step to speed convergence on solu
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Spatial reasoning with genetic algorithms an application in planning of safe Liquid Petroleum Gas sven area, of arbitrary shape, without contravening the safety distances. The genetic algorithm was able to produce interesting and safe layouts, and merits further investigation for more complicated problems. The genetic algorithm used involved a local hill-climbing step to speed convergence on solu
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https://doi.org/10.1007/BFb0032768artificial intelligence; evolution; genetic programming; image processing; intelligence; learning; program
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https://doi.org/10.1057/9781137313799but, where the proposed synthesis consist of many individual steps, there is also a combinatorial difficulty to be solved. This paper discusses the use of a modified ant system algorithm to tackle the synthetic design problem.
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