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Genetic Programming Theory and Practice XII

  • Book
  • © 2015

Overview

Editors:
  1. Rick Riolo

    1. Center for the Study of Complex Systems (CSCS), University of Michigan, Ann Arbor, USA

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  2. William P. Worzel

    1. Evolution Enterprises, Milan, USA

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    You can also search for this editor in PubMed   Google Scholar

  3. Mark Kotanchek

    1. Evolved Analytics, Midland, USA

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    You can also search for this editor in PubMed   Google Scholar

  • Provides papers describing cutting-edge work on genetic programming theory, applications of GP and theory
  • Offers large-scale, real-world applications of GP to a variety of problem domains, from financial engineering to analog circuit design
  • Based on cutting edge applications and the latest in theoretical results
  • Includes supplementary material: sn.pub/extras

Part of the book series: Genetic and Evolutionary Computation (GEVO)

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xii
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  2. Application of Machine-Learning Methods to Understand Gene Expression Regulation

    • Chao Cheng, William P. Worzel
    Pages 1-15

  3. Identification of Novel Genetic Models of Glaucoma Using the “EMERGENT” Genetic Programming-Based Artificial Intelligence System

    • Jason H. Moore, Casey S. Greene, Douglas P. Hill
    Pages 17-35

  4. Inheritable Epigenetics in Genetic Programming

    • William La Cava, Lee Spector
    Pages 37-51

  5. SKGP: The Way of the Combinator

    • William P. Worzel, Duncan MacLean
    Pages 53-71

  6. Sequential Symbolic Regression with Genetic Programming

    • Luiz Otávio V.B. Oliveira, Fernando E.B. Otero, Gisele L. Pappa, Julio Albinati
    Pages 73-90

  7. Sliding Window Symbolic Regression for Detecting Changes of System Dynamics

    • Stephan M. Winkler, Michael Affenzeller, Gabriel Kronberger, Michael Kommenda, Bogdan Burlacu, Stefan Wagner
    Pages 91-107

  8. Extremely Accurate Symbolic Regression for Large Feature Problems

    • Michael F. Korns
    Pages 109-131

  9. How to Exploit Alignment in the Error Space: Two Different GP Models

    • Mauro Castelli, Leonardo Vanneschi, Sara Silva, Stefano Ruberto
    Pages 133-148

  10. Analyzing a Decade of Human-Competitive (“HUMIE”) Winners: What Can We Learn?

    • Karthik Kannappan, Lee Spector, Moshe Sipper, Thomas Helmuth, William La Cava, Jake Wisdom et al.
    Pages 149-166

  11. Tackling the Boolean Multiplexer Function Using a Highly Distributed Genetic Programming System

    • Hormoz Shahrzad, Babak Hodjat
    Pages 167-179

  12. Back Matter

    Pages 181-182
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Keywords

About this book

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: gene expression regulation, novel genetic models for glaucoma, inheritable epigenetics, combinators in genetic programming, sequential symbolic regression, system dynamics, sliding window symbolic regression, large feature problems, alignment in the error space, HUMIE winners, Boolean multiplexer function, and highly distributed genetic programming systems. Application areas include chemical process control, circuit design, financial data mining and bioinformatics. 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.

Editors and Affiliations

  • Center for the Study of Complex Systems (CSCS), University of Michigan, Ann Arbor, USA

    Rick Riolo

  • Evolution Enterprises, Milan, USA

    William P. Worzel

  • Evolved Analytics, Midland, USA

    Mark Kotanchek

Bibliographic Information

  • Book Title: Genetic Programming Theory and Practice XII

  • Editors: Rick Riolo, William P. Worzel, Mark Kotanchek

  • Series Title: Genetic and Evolutionary Computation

  • DOI: https://doi.org/10.1007/978-3-319-16030-6

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer International Publishing Switzerland 2015

  • Hardcover ISBN: 978-3-319-16029-0Published: 25 June 2015

  • Softcover ISBN: 978-3-319-38376-7Published: 17 October 2016

  • eBook ISBN: 978-3-319-16030-6Published: 04 June 2015

  • Series ISSN: 1932-0167

  • Series E-ISSN: 1932-0175

  • Edition Number: 1

  • Number of Pages: XII, 182

  • Number of Illustrations: 47 b/w illustrations, 12 illustrations in colour

  • Topics: Artificial Intelligence, Algorithm Analysis and Problem Complexity, Programming Techniques

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