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Titlebook: Genetic Programming Theory and Practice XV; Wolfgang Banzhaf,Randal S. Olson,Rick Riolo Conference proceedings 2018 Springer International

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書目名稱Genetic Programming Theory and Practice XV
編輯Wolfgang Banzhaf,Randal S. Olson,Rick Riolo
視頻videohttp://file.papertrans.cn/383/382611/382611.mp4
概述Provides papers describing cutting-edge work on the theory and applications of genetic programming (GP).Offers large-scale, real-world applications (big data) of GP to a variety of problem domains, in
叢書名稱Genetic and Evolutionary Computation
圖書封面Titlebook: Genetic Programming Theory and Practice XV; Wolfgang Banzhaf,Randal S. Olson,Rick Riolo Conference proceedings 2018 Springer International
描述.These contributions, written by the foremost international researchers and practitioners of Genetic Programming (GP), explore the synergy between theoretical and empirical results on real-world problems, producing a comprehensive view of the state of the art in GP. Topics in this volume include: exploiting subprograms in genetic programming, schema frequencies in GP, Accessible AI, GP for Big Data, lexicase selection, symbolic regression techniques, co-evolution of GP and LCS, and applying ecological principles to GP. It also covers several chapters on best practices and lessons learned from hands-on experience. 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..
出版日期Conference proceedings 2018
關(guān)鍵詞Genetic Programming; Genetic Programming Theory; Genetic Programming Applications; Symbolic Regression;
版次1
doihttps://doi.org/10.1007/978-3-319-90512-9
isbn_softcover978-3-030-08031-0
isbn_ebook978-3-319-90512-9Series ISSN 1932-0167 Series E-ISSN 1932-0175
issn_series 1932-0167
copyrightSpringer International Publishing AG, part of Springer Nature 2018
The information of publication is updating

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Lexicase Selection with Weighted Shuffle,election, a semantic-aware selection, randomly shuffles the list of test cases and places more emphasis on those test cases that randomly appear earlier in the ordering than those that appear later in the ordering. In this work, we explore methods for weighting this shuffling of test cases to give s
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Relaxations of Lexicase Parent Selection,of which new programs will be constructed. The lexicase parent selection algorithm chooses a parent by considering all test cases, individually, one at a time, in a random order, to reduce the pool of possible parent programs. Lexicase selection is ordinarily strict, in that a program can only be se
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