Genetic Programming Theory and Practice IV
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Beschreibung
Genetic Programming Theory and Practice IV was developed from the fourth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.
This valuable reference discusses the hurdles faced in solving large-scale, cutting edge applications, describes promising techniques, including fitness approximation, Pareto optimization, cooperative teams, solution caching, and experiment control, and investigates evolutionary approaches such as financial modeling, bioinformatics, symbolic regression for system modeling, and evolutionary design of circuits and robot controllers.
Genetic Programming Theory and Practice IV represents a watershed moment in the GP field in that GP has begun to move from hand-crafted software used primarily in academic research, to an engineering methodology applied to commercial applications. It is a unique and indispensable tool for academics, researchers and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.
Genetic Programming Theory and Practice IV was developed from the fourth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). The text provides a cohesive view of the issues facing both practitioners and theoreticians, and examines the synergy between GP theory and application. The foremost international researchers and practitioners in the GP arena contributed to the volume, exploring application areas including chemical process control, circuit design, financial data mining and bioinformatics, to name just a few.
This volume is the result of an extensive dialog between GP theoreticians and practitioners, and is a unique and indispensable tool for both academics and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.
Discusses the hurdles faced in solving large-scale, cutting edge applications Describes promising techniques, including fitness approximation, Pareto optimization, cooperative teams, solution caching, and experiment control Explores evolutionary approaches such as financial modeling, bioinformatics, symbolic regression for system modeling, and evolutionary design of circuits and robot controllers Includes supplementary material: sn.pub/extras
Autor*in
Rick Riolo
Themen in »Genetic Programming Theory and Practice IV«
Automat Boosting algorithm algorithms artificial intelligence classification complex system genetic algorithms learning machine learning modeling optimization programming robot stability
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From the reviews:
"Every cutting-edge researcher, in every computational discipline, working on any real-world application, should make it a point to keep abreast of the ongoing progress of genetic programming theory and practice, which is currently available in this book. … a great win-win synergy opportunity here for less-cutting-edge researchers to try these maturing tools on more intuitive data masses; they should be more able to appreciate the results, and the genetic programming cryptography community might then learn something new about how to interpret post-scientific results." (Chaim Scheff, ACM Computing Reviews, Vol. 49 (8), August, 2008)
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