Genetic Programming Theory and Practice XIII

W.P. Worzel (Hrsg.), Mark Kotanchek (Hrsg.), Arthur Kordon (Hrsg.), Rick Riolo (Hrsg.)

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik


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: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. 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.

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Hyper heuristics, Symbolic regression, Singularity, Semantic programming, Feature generation, Machine learning, Multi-objective optimization, Big data, Genetic programming, Data science, Geometric programming, Lexicase selection, Cloud computing, Evolutionary algorithms