Genetic Programming Theory and Practice XIII
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Beschreibung
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. Topics in this volume include: multi-objective genetic programming, learning heuristics, Kaizen programming, Evolution of Everything (EvE), lexicase selection, behavioral program synthesis, symbolic regression with noisy training data, graph databases, and multidimensional clustering. It also covers several chapters on best practices and lesson learned from hands-on experience. Additional application areas include financial operations, genetic analysis, and predicting product choice. 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 papers 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, including financial applications, genetic analysis, product selection Theoretical exploration of controlled semantic, lexicase and other selection and crossover methods, and understanding convergence Includes supplementary material: sn.pub/extras
Autor*in
Rick Riolo
Themen in »Genetic Programming Theory and Practice XIII«
Feature generation Genetic programming Symbolic regression Machine learning Evolutionary algorithms Semantic programming Geometric programming Big data Cloud computing Data science Hyper heuristics Multi-objective optimization Lexicase selection Singularity algorithm analysis and problem complexity