Genetic and Evolutionary Computation

Genetic Programming Theory and Practice V

Editors: Riolo, Rick, Soule, Terence, Worzel, Bill (Eds.)

  • Discusses hurdles in solving large-scale applications
  • Describes techniques including fitness and age layered populations, code reuse through caching, archives and libraries, Pareto optimization, pre- and post-processing, the use of expert knowledge and information-theoretic fitness measures
  • Addresses practical methods for choosing between techniques for improving GP performance and to evolve trustable solutions
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About this book

Genetic Programming Theory and Practice V was developed from the fifth workshop at the University of Michigan’s Center for the Study of Complex Systems to facilitate the exchange of ideas and information related to the rapidly advancing field of Genetic Programming (GP). Contributions from the foremost international researchers and practitioners in the GP arena examine the similarities and differences between theoretical and empirical results on real-world problems. The text explores the synergy between theory and practice, producing a comprehensive view of the state of the art in GP application.

Specific topics addressed in the book include:

  • the hurdles faced in solving large-scale, cutting edge applications
  • promising techniques, including fitness and age layered populations, code reuse through caching, archives and run transferable libraries, Pareto optimization, and pre- and post-processing
  • the use of information theoretic measures and ensemble techniques
  • approaches to help GP create trustable solutions
  • the use of expert knowledge to guide GP
  • ways to make GP tools more accessible to the non-GP-expert
  • practical methods for understanding and choosing between the recent proliferation of techniques for improving GP performance
  • the potential for GP to undergo radical changes to accommodate the expanded understanding of biological genetics and evolution

The work covers applications of GP to a wide variety of domains, including bioinformatics, symbolic regression for system modeling, financial modeling, circuit design and robot controllers. This volume is a unique and indispensable tool for academics, researchers and industry professionals involved in GP, evolutionary computation, machine learning and artificial intelligence.

Table of contents (15 chapters)

  • Genetic Programming: Theory and Practice

    Soule, Terence (et al.)

    Pages 1-12

  • Better Solutions Faster: Soft Evolution of Robust Regression Models InParetogeneticprogramming

    Vladislavleva, Ekaterina (et al.)

    Pages 13-32

  • Manipulation of Convergence in Evolutionary Systems

    Murphy, Gearoid (et al.)

    Pages 33-52

  • Large-Scale, Time-Constrained Symbolic Regression-Classification

    Korns, Michael F.

    Pages 53-68

  • Solving Complex Problems in Human Genetics Using Genetic Programming: The Importance of Theorist-Practitionercomputer Interaction

    Moore, Jason H. (et al.)

    Pages 69-85

Buy this book

eBook $119.00
price for USA
  • ISBN 978-0-387-76308-8
  • Digitally watermarked, DRM-free
  • Included format: PDF
  • ebooks can be used on all reading devices
  • Download immediately after purchase
Hardcover $159.00
price for USA
  • ISBN 978-0-387-76307-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Softcover $159.00
price for USA
  • ISBN 978-1-4419-4547-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Genetic Programming Theory and Practice V
Editors
  • Rick Riolo
  • Terence Soule
  • Bill Worzel
Series Title
Genetic and Evolutionary Computation
Copyright
2008
Publisher
Springer US
Copyright Holder
Springer-Verlag US
eBook ISBN
978-0-387-76308-8
DOI
10.1007/978-0-387-76308-8
Hardcover ISBN
978-0-387-76307-1
Softcover ISBN
978-1-4419-4547-1
Series ISSN
1932-0167
Edition Number
1
Number of Pages
XIV, 279
Topics