Genetic Programming Theory and Practice XV

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: exploiting subprograms in genetic programming, schema frequencies in GP, Accessible AI, GP for Big Data, lexicase selection, symbolic regression techniques, co-evolution of GP and LCS, and applying ecological principles to GP. It also covers several chapters on best practices and lessons learned from hands-on experience. 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.

Zusammenfassung

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: exploiting subprograms in genetic programming, schema frequencies in GP, Accessible AI, GP for Big Data, lexicase selection, symbolic regression techniques, co-evolution of GP and LCS, and applying ecological principles to GP. It also covers several chapters on best practices and lessons learned from hands-on experience. 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.

Produktdetails

• Mitarbeit: Wolfgang Banzhaf (Herausgeber), Randal S. Olson (Herausgeber), Rick Riolo (Herausgeber), Randa S Olson (Herausgeber), Randal S Olson (Herausgeber), William Tozier (Herausgeber), William Tozier et al (Herausgeber)
• Verlag: Springer, Berlin
• Sprache: Englisch
• Produktform: Taschenbuch
• Erschienen: 01.01.2018
• EAN: 9783030080310
• ISBN: 978-3-0-3008031-0
• Seiten: 187
• Abmessung: 155 mm x 11 mm x 235 mm
• Gewicht: 320 g
• Illustration: XV, 187 p. 54 illus., 46 illus. in color.
• Serie: Genetic and Evolutionary Computation
• Themen: Naturwissenschaften, Medizin, Informatik, Technik > Informatik, EDV > Informatik; C, Algorithmen und Datenstrukturen, machine learning, Algorithms, Artificial Intelligence, computer science, data analysis, Theory of Computation, Algorithms & data structures, Computational Intelligence, Algorithm Analysis and Problem Complexity