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.