Rick Riolo & Bill Worzel 
Genetic Programming Theory and Practice XIV [PDF ebook] 

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 Push GP 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.

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