Genetic Programming Theory and Practice XVI

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ISBN 10: 3030047342 / ISBN 13: 9783030047344

Published by Springer, 2019

About this Item

Zustand: Hervorragend | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | 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.

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Bibliographic Details

• Title: Genetic Programming Theory and Practice XVI
• Publisher: Springer
• Publication Date: 2019
• Language: English
• ISBN 10: 3030047342
• ISBN 13: 9783030047344
• Binding: Hardcover
• Condition: Hervorragend
• Seller catalogs:
  • Bücher

About this title

Synopsis

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.