Genetic Programming Theory and Practice XIV

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:

• Similarity-based Analysis of Population Dynamics in GP Performing Symbolic Regression

• Hybrid Structural and Behavioral Diversity Methods in GP

• Multi-Population Competitive Coevolution for Anticipation of Tax Evasion

• Evolving Artificial General Intelligence for Video Game Controllers

• A Detailed Analysis of a PushGP Run

• Linear Genomes for Structured Programs

• Neutrality, Robustness, and Evolvability in GP

• Local Search in GP

• PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification

• Relational Structure in Program Synthesis Problems with Analogical Reasoning

• An Evolutionary Algorithm for Big Data Multi-Class Classification Problems

• A Generic Framework for Building Dispersion Operators in the Semantic Space

• 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.

  Provides chapters describing cutting-edge work on the theory and applications of genetic programming (GP) Offers large-scale, real-world applications of GP to a variety of problem domains Written by leading international experts from both academia and industry

  Zusammenfassung
  "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)

  Inhalt
  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.