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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.
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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