Genetic Programming Theory and Practice XVI

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, General Computing, Programming
Cover of the book Genetic Programming Theory and Practice XVI by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783030047351
Publisher: Springer International Publishing Publication: January 23, 2019
Imprint: Springer Language: English
Author:
ISBN: 9783030047351
Publisher: Springer International Publishing
Publication: January 23, 2019
Imprint: Springer
Language: English

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: evolving developmental programs for neural networks solving multiple problems, tangled program, transfer learning and outlier detection using GP, program search for machine learning pipelines in reinforcement learning, automatic programming with GP, new variants of GP, like SignalGP, variants of lexicase selection, and symbolic regression and classification techniques. The volume includes 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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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: evolving developmental programs for neural networks solving multiple problems, tangled program, transfer learning and outlier detection using GP, program search for machine learning pipelines in reinforcement learning, automatic programming with GP, new variants of GP, like SignalGP, variants of lexicase selection, and symbolic regression and classification techniques. The volume includes 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.

More books from Springer International Publishing

Cover of the book Models, Algorithms, and Technologies for Network Analysis by
Cover of the book Uranium in Plants and the Environment by
Cover of the book The Arrhythmic Patient in the Emergency Department by
Cover of the book Chemical Reactions by
Cover of the book Thermo-Hydro-Mechanical-Chemical Processes in Fractured Porous Media: Modelling and Benchmarking by
Cover of the book Hybrid Metaheuristics by
Cover of the book Solar to Chemical Energy Conversion by
Cover of the book The Vienna Circle by
Cover of the book Quantum Chemical Approach for Organic Ferromagnetic Material Design by
Cover of the book Computer Vision, Imaging and Computer Graphics Theory and Applications by
Cover of the book EPSA15 Selected Papers by
Cover of the book Continuous Media with Microstructure 2 by
Cover of the book AI*IA 2017 Advances in Artificial Intelligence by
Cover of the book Advanced Polymers in Medicine by
Cover of the book Nile Waters, Saharan Sands by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy