Genetic Programming Theory and Practice XVII (eBook)

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Autor: Wolfgang (Hrsg.) Banzhaf

CHF 189.00

ISBN: 978-3-030-39958-0

Einband: PDF

Verfügbarkeit: Download, sofort verfügbar (Link per E-Mail)

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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. In this year's edition, the topics covered include many of the most important issues and research questions in the ¿eld, such as: opportune application domains for GP-based methods, game playing and co-evolutionary search, symbolic regression and ef¿cient learning strategies, encodings and representations for GP, schema theorems, and new selection mechanisms.The volume includes 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.

Autor	Banzhaf, Wolfgang (Hrsg.) / Goodman, Erik (Hrsg.) / Sheneman, Leigh (Hrsg.) / Trujillo, Leonardo (Hrsg.) / Worzel, Bill (Hrsg.)
Verlag	Springer International Publishing
Einband	PDF
Erscheinungsjahr	2020
Seitenangabe	409 S.
Ausgabekennzeichen	Englisch
Abbildungen	XXVI, 409 p. 142 illus., 112 illus. in color.
Auflage	1st ed. 2020

Über den Autor Wolfgang (Hrsg.) Banzhaf

Wolfgang Banzhaf is a professor in the Department of Computer Science and Engineering at Michigan State University. He is the John R. Koza Endowed Chair in Genetic Programming and a member of the BEACON Center for the Study of Evolution in Action. His research interests include evolutionary computation and complex adaptive systems. Studies of self-organization and the field of Artificial Life are also of very much interest to him. Penousal Machado is an associate professor in the Department of Informatics at the University of Coimbra in Portugal, the coordinator of the Cognitive and Media Systems group of the Centre for Informatics and Systems of the University of Coimbra (CISUC), and the scientific director of the Computational Design and Visualization Lab of CISUC. His research interests include evolutionary computation, computational creativity, artificial intelligence, and information visualization. Mengjie Zhang is a Professor of Computer Science, Head of the Evolutionary Computation and machine learning Research Group, and Director of Data Science and Artificial Intelligence, Victoria University of Wellington, New Zealand. His current research interests include artificial intelligence and machine learning, particularly genetic programming, image analysis, feature selection and reduction, job shop scheduling, and transfer learning.