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Genetic Programming Theory and Practice XIII

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

Buch | Hardcover

XX, 262 Seiten

2016 | 1st ed. 2016
Springer International Publishing (Verlag)
978-3-319-34221-4 (ISBN)

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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.

Evolving Simple Symbolic Regression Models by Multi-objective Genetic Programming.- Learning Heuristics for Mining RNA Sequence-Structure Motifs.- Kaizen Programming for Feature Construction for Classification.- GP as if You Meant It: An Exercise for Mindful Practice.- nPool: Massively Distributed Simultaneous Evolution and Cross-Validation in EC-Star.- Highly Accurate Symbolic Regression with Noisy Training Data.- Using Genetic Programming for Data Science: Lessons Learned.- The Evolution of Everything (EvE) and Genetic Programming.- Lexicase selection for program synthesis: a Diversity Analysis.- Using Graph Databases to Explore the Dynamics of Genetic Programming Runs.- Predicting Product Choice with Symbolic Regression and Classification.- Multiclass Classification Through Multidimensional Clustering.- Prime-Time: Symbolic Regression takes its place in the Real World.

Erscheinungsdatum	17.09.2016
Reihe/Serie	Genetic and Evolutionary Computation
Zusatzinfo	XX, 262 p. 69 illus., 31 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Informatik ► Theorie / Studium ► Algorithmen
	Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik
	Wirtschaft ► Betriebswirtschaft / Management
Schlagworte	Algorithm analysis and problem complexity • artificial intelligence (incl. robotics) • Big Data • Cloud Computing • Computational Intelligence • Computer Science • Data Science • evolutionary algorithms • Feature Generation • genetic programming • geometric programming • Hyper heuristics • Lexicase selection • machine learning • Multi-Objective Optimization • Operations Research, Management Science • semantic programming • Singularity • Symbolic Regression
ISBN-10	3-319-34221-5 / 3319342215
ISBN-13	978-3-319-34221-4 / 9783319342214
Zustand	Neuware