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Titlebook: Evolutionary Optimization: the μGP toolkit; Ernesto Sanchez,Massimiliano Schillaci,Giovanni Sq Book 2011 Springer Science+Business Media,

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書目名稱Evolutionary Optimization: the μGP toolkit
編輯Ernesto Sanchez,Massimiliano Schillaci,Giovanni Sq
視頻videohttp://file.papertrans.cn/318/317996/317996.mp4
概述Describes an award-winning evolutionary algorithm used for solving practical problems in industry.Provides a practical guide on using the μGP, a set of examples to clarify the available choices and ad
圖書封面Titlebook: Evolutionary Optimization: the μGP toolkit;  Ernesto Sanchez,Massimiliano Schillaci,Giovanni Sq Book 2011 Springer Science+Business Media,
描述.This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled μGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers..For a practitioner, μGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results..For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested..MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/.
出版日期Book 2011
關(guān)鍵詞Evolutionary Optimization; Genetic Programming; Graph-based representation; Industrial Problems; MicroGP
版次1
doihttps://doi.org/10.1007/978-0-387-09426-7
isbn_softcover978-1-4899-9368-7
isbn_ebook978-0-387-09426-7
copyrightSpringer Science+Business Media, LLC 2011
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hering results..For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested..MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/.978-1-4899-9368-7978-0-387-09426-7
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Ernesto Sanchez,Massimiliano Schillaci,Giovanni SqDescribes an award-winning evolutionary algorithm used for solving practical problems in industry.Provides a practical guide on using the μGP, a set of examples to clarify the available choices and ad
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https://doi.org/10.1007/978-1-4302-6008-0due to modifications inherited through successive generations. . is the offshoot of computer science focusing on algorithms inspired by the theory of evolution. The definition is deliberately vague since the boundaries of the field are not, and cannot be, defined clearly. Evolutionary computation is
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Driving Automation Through Monitoring,d, making changes local to a single file, without affecting global parameters. The user may even want to prepare several different files specifying the population parameters, and then switch between them by changing the settings, as described in chapter 7.
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