Genetic Programming Theory and Practice XIII

Rick Riolo

ISBN 10: 3319342215 / ISBN 13: 9783319342214

Verlag: Springer International Publishing, Springer International Publishing Dez 2016, 2016

Beschreibung

Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 284 pp. Englisch.

Bestandsnummer des Verkäufers 9783319342214

Bibliografische Details

• Titel: Genetic Programming Theory and Practice XIII
• Verlag: Springer International Publishing, Springer International Publishing Dez 2016
• Erscheinungsjahr: 2016
• Sprache: Englisch
• ISBN-10: 3319342215
• ISBN-13: 9783319342214
• Einband: Buch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

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.