Genetic Programming Theory and Practice VIII 2011th Edition
Author(s): Rick Riolo (Editor), Trent McConaghy (Editor), Ekaterina Vladislavleva (Editor)
Publisher: Springer
Publication Date: December 1, 2012
Edition: 2011th
Language: English
Print length: 276 pages
ISBN-10: 1461427193
ISBN-13: 9781461427193
Book Description
The contributions in this volume are written by the foremost international researchers and practitioners in the GP arena. They 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.
Topics include: FINCH: A System for Evolving Java, Practical Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution of Teams, Self-modifying Cartesian GP, Abstract Expression Grammar Symbolic Regression, Age-Fitness Pareto Optimization, Scalable Symbolic Regression by Continuous Evolution, Symbolic Density Models, GP Transforms in Linear Regression Situations, Protein Interactions in a Computational Evolution System, Composition of Music and Financial Strategies via GP, and Evolutionary Art Using Summed Multi-Objective Ranks.
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 in GP .
Editorial Reviews
Review
From the reviews:
“The book consists of 14 papers and an introduction. The applications it considers clearly demonstrate the maturity of GP techniques, and their ability to efficiently address difficult problem instances. … A specialized audience of experts in genetic algorithms will find state-of-the-art applications and methodologies in this book. It will also be of interest to practitioners for the large number of applications discussed, and to advanced students and researchers for the numerous opportunities for investigation and thesis topics.” (Renato De Leone, ACM Computing Reviews, July, 2011)
Genetic Programming Theory and Practice VIII 2011th Edition
Author(s): Rick Riolo (Editor), Trent McConaghy (Editor), Ekaterina Vladislavleva (Editor)
Publisher: Springer
Publication Date: October 28, 2010
Edition: 2011th
Language: English
Print length: 276 pages
ISBN-10: 1441977465
ISBN-13: 9781441977465
Book Description
The contributions in this volume are written by the foremost international researchers and practitioners in the GP arena. They 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.
Topics include: FINCH: A System for Evolving Java, Practical Autoconstructive Evolution, The Rubik Cube and GP Temporal Sequence Learning, Ensemble classifiers: AdaBoost and Orthogonal Evolution of Teams, Self-modifying Cartesian GP, Abstract Expression Grammar Symbolic Regression, Age-Fitness Pareto Optimization, Scalable Symbolic Regression by Continuous Evolution, Symbolic Density Models, GP Transforms in Linear Regression Situations, Protein Interactions in a Computational Evolution System, Composition of Music and Financial Strategies via GP, and Evolutionary Art Using Summed Multi-Objective Ranks.
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 in GP .
Editorial Reviews
Review
From the reviews:
“The book consists of 14 papers and an introduction. The applications it considers clearly demonstrate the maturity of GP techniques, and their ability to efficiently address difficult problem instances. … A specialized audience of experts in genetic algorithms will find state-of-the-art applications and methodologies in this book. It will also be of interest to practitioners for the large number of applications discussed, and to advanced students and researchers for the numerous opportunities for investigation and thesis topics.” (Renato De Leone, ACM Computing Reviews, July, 2011)
Genetic Programming Theory and Practice IX 2011th Edition
Author(s): Rick Riolo (Editor), Ekaterina Vladislavleva (Editor), Jason H. Moore (Editor)
Publisher: Springer
Publication Date: November 1, 2011
Edition: 2011th
Language: English
Print length: 292 pages
ISBN-10: 1461417694
ISBN-13: 9781461417699
Book Description
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 include: modularity and scalability; evolvability; human-competitive results; the need for important high-impact GP-solvable problems;; the risks of search stagnation and of cutting off paths to solutions; the need for novelty; empowering GP search with expert knowledge; In addition, GP symbolic regression is thoroughly discussed, addressing such topics as guaranteed reproducibility of SR; validating SR results, measuring and controlling genotypic complexity; controlling phenotypic complexity; identifying, monitoring, and avoiding over-fitting; finding a comprehensive collection of SR benchmarks, comparing SR to machine learning. This text is for all GP explorers. 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.
Genetic Programming Theory and Practice IX 2011th Edition
Author(s): Rick Riolo (Editor), Ekaterina Vladislavleva (Editor), Jason H. Moore (Editor)
Publisher: Springer
Publication Date: November 29, 2013
Edition: 2011th
Language: English
Print length: 292 pages
ISBN-10: 1461429412
ISBN-13: 9781461429418
Book Description
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 include: modularity and scalability; evolvability; human-competitive results; the need for important high-impact GP-solvable problems;; the risks of search stagnation and of cutting off paths to solutions; the need for novelty; empowering GP search with expert knowledge; In addition, GP symbolic regression is thoroughly discussed, addressing such topics as guaranteed reproducibility of SR; validating SR results, measuring and controlling genotypic complexity; controlling phenotypic complexity; identifying, monitoring, and avoiding over-fitting; finding a comprehensive collection of SR benchmarks, comparing SR to machine learning. This text is for all GP explorers. 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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