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. Chapters in this volume include:
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Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression
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Hybrid Structural and Behavioral Diversity Methods in GP
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Multi-Population Competitive Coevolution for Anticipation of Tax Evasion
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Evolving Artificial General Intelligence for Video Game Controllers
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A Detailed Analysis of a PushGP Run
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Linear Genomes for Structured Programs
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Neutrality, Robustness, and Evolvability in GP
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Local Search in GP
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PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification
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Relational Structure in Program Synthesis Problems with Analogical Reasoning
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An Evolutionary Algorithm for Big Data Multi-Class Classification Problems
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A Generic Framework for Building Dispersion Operators in the Semantic Space
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Assisting Asset Model Development with Evolutionary Augmentation
- Building Blocks of Machine Learning Pipelines for Initialization of a Data Science Automation Tool
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.
Rezensionen / Stimmen
"This highly technical book is meant for a very specialized audience: researchers in GP. The topics discussed offer interesting insight into how research in GP is evolving. . I strongly recommend this book for researchers in evolutionary computing and GP." (S. V. Nagaraj, Computing Reviews, November 12, 2020)
Reihe
Sprache
Verlagsort
Verlagsgruppe
Springer International Publishing
Illustrationen
52 s/w Abbildungen
XV, 227 p. 52 illus.
Dateigröße
ISBN-13
978-3-319-97088-2 (9783319970882)
DOI
10.1007/978-3-319-97088-2
Schweitzer Klassifikation
1 Similarity-based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression.- 2 An Investigation of Hybrid Structural and Behavioral Diversity Methods in Genetic Programming.- 3 Investigating Multi-Population Competitive Coevolution for Anticipation of Tax Evasion.- 4 Evolving Artificial General Intelligence for Video Game Controllers.- 5 A Detailed Analysis of a PushGP Run.- 6 Linear Genomes for Structured Programs.- 7 Neutrality, Robustness, and Evolvability in Genetic Programming.- 8 Local Search is Underused in Genetic Programming.- 9 PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification.- 10 Discovering Relational Structural in Program Synthesis Problems with Analogical Reasoning.- 11 An Evolutionary Algorithm for Big Data Multi-Class Classification Problems.- 12 A Genetic Framework for Building Dispersion Operators in the Semantic Space.- 13 Assisting Asset Model Development with Evolutionary Augmentation.- 14 Identifying andHarnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool.