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Titlebook: Genetic Programming Theory and Practice VIII; Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva Book 2011 Springer Science+Business Media

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書目名稱Genetic Programming Theory and Practice VIII
編輯Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva
視頻videohttp://file.papertrans.cn/383/382604/382604.mp4
概述Presents large-scale, real-world applications of GP.Addresses a variety of problem domains that respond to GP solutions.Written by leading researchers and practitioners in the field.Includes supplemen
叢書名稱Genetic and Evolutionary Computation
圖書封面Titlebook: Genetic Programming Theory and Practice VIII; Rick Riolo,Trent McConaghy,Ekaterina Vladislavleva Book 2011 Springer Science+Business Media
描述.The contributions in this volume are written by the foremost international researchers and practitioners in the GP arena. They examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application..Topics include: FINCH: A System for Evolving Java, Practical Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution of Teams, Self-modifying Cartesian GP, Abstract Expression Grammar Symbolic Regression, Age-Fitness Pareto Optimization, Scalable Symbolic Regression by Continuous Evolution, Symbolic Density Models, GP Transforms in Linear Regression Situations, Protein Interactions in a Computational Evolution System, Composition of Music and Financial Strategies via GP, and Evolutionary Art Using Summed Multi-Objective Ranks..Readers will discover large-scale, real-world applications of GP to a variety of problem domains via in-depth presentations of the latest and most significant results in GP ..
出版日期Book 2011
關(guān)鍵詞Genetic Programming; Genetic Programming Applications; Genetic Programming Theory; Symbolic regression;
版次1
doihttps://doi.org/10.1007/978-1-4419-7747-2
isbn_softcover978-1-4614-2719-3
isbn_ebook978-1-4419-7747-2Series ISSN 1932-0167 Series E-ISSN 1932-0175
issn_series 1932-0167
copyrightSpringer Science+Business Media, LLC 2011
The information of publication is updating

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Symbolic Density Models of One-in-a-Billion Statistical Tails via Importance Sampling and Genetic P to analyze the tradeoff between high-sigma yields and circuit performance. The flow is validated on two modern industrial problems: a bitcell circuit on a 45nm TSMC process, and a sense amp circuit on a 28nm TSMC process.
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Das Aufbereiten von Textausgabenety of different problems, and see that SMCGP is able to solve tasks that require scalability and plasticity. We demonstrate how SMCGP is able to produce results that would be impossible for conventional, static Genetic Programming techniques.
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Finch: A System for Evolving Java (Bytecode),eral. This is in contrast to existing work that uses restricted subsets of the Java bytecode instruction set as a representation language for individuals in genetic programming. The ability to evolve Java programs will hopefully lead to a valuable new tool in the software engineer’s toolkit.
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A Survey of Self Modifying Cartesian Genetic Programming,ety of different problems, and see that SMCGP is able to solve tasks that require scalability and plasticity. We demonstrate how SMCGP is able to produce results that would be impossible for conventional, static Genetic Programming techniques.
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