Genetic Programming Theory and Practice VI

Genetic Programming Theory and Practice VI was developed from the sixth workshop at the University of Michigan's Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP).Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.These contributions address several significant inter-dependent themes which emerged from this year's workshop, including:Making efficient and effective use of test dataSustaining the long term evolvability of our GP systemsExploiting discovered subsolutions for reuseIncreasing the role of a Domain ExpertIn the course of investigating these themes, the chapters describe a variety of techniques in widespread use among practitioners who deal with industrial-scale, real-world problems, such as: Pareto optimization, particularly as a means to limit solution complexityVarious types of age-layered populations or niching mechanismsData partitioning, a priori or adaptively, e.g., via co-evolutionCluster computing or general purpose graphics processors for parallel computingEnsemble/team solutionsThis work covers applications of GP to a host of domains, including bioinformatics, symbolic regression for system modeling in various settings, circuit design, and financial modeling to support portfolio management.This volume is a unique and indispensable tool for academics, researchers and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.