Genetic Programming Theory and Practice XIV

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. 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. Front Matter ....Pages i-xv Similarity-Based Analysis of Population Dynamics in Genetic Programming Performing Symbolic Regression (Stephan M. Winkler, Michael Affenzeller, Bogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Philipp Fleck)....Pages 1-17 An Investigation of Hybrid Structural and Behavioral Diversity Methods in Genetic Programming (Armand R. Burks, William F. Punch)....Pages 19-34 Investigating Multi-Population Competitive Coevolution for Anticipation of Tax Evasion (Erik Hemberg, Jacob Rosen, Una-May O’Reilly)....Pages 35-51 Evolving Artificial General Intelligence for Video Game Controllers (Itay Azaria, Achiya Elyasaf, Moshe Sipper)....Pages 53-63 A Detailed Analysis of a PushGP Run (Nicholas Freitag McPhee, Mitchell D. Finzel, Maggie M. Casale, Thomas Helmuth, Lee Spector)....Pages 65-83 Linear Genomes for Structured Programs (Thomas Helmuth, Lee Spector, Nicholas Freitag McPhee, Saul Shanabrook)....Pages 85-100 Neutrality, Robustness, and Evolvability in Genetic Programming (Ting Hu, Wolfgang Banzhaf)....Pages 101-117 Local Search is Underused in Genetic Programming (Leonardo Trujillo, Emigdio Z-Flores, Perla S. Juárez-Smith, Pierrick Legrand, Sara Silva, Mauro Castelli et al.)....Pages 119-137 PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification (Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, Chris Holmes)....Pages 139-148 Discovering Relational Structure in Program Synthesis Problems with Analogical Reasoning (Jerry Swan, Krzysztof Krawiec)....Pages 149-164 An Evolutionary Algorithm for Big Data Multi-Class Classification Problems (Michael F. Korns)....Pages 165-178 A Generic Framework for Building Dispersion Operators in the Semantic Space (Luiz Otavio V. B. Oliveira, Fernando E. B. Otero, Gisele L. Pappa)....Pages 179-195 Assisting Asset Model Development with Evolutionary Augmentation (Steven Gustafson, Arun Subramaniyan, Aisha Yousuf)....Pages 197-210 Identifying and Harnessing the Building Blocks of Machine Learning Pipelines for Sensible Initialization of a Data Science Automation Tool (Randal S. Olson, Jason H. Moore)....Pages 211-223 Back Matter ....Pages 225-227