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Genetic Programming and Evolvable Machines

, Volume 11, Issue 3–4, pp 285–320 | Cite as

Theoretical results in genetic programming: the next ten years?

  • Riccardo Poli
  • Leonardo Vanneschi
  • William B. Langdon
  • Nicholas Freitag McPhee
Contributed article

Abstract

We consider the theoretical results in GP so far and prospective areas for the future. We begin by reviewing the state of the art in genetic programming (GP) theory including: schema theories, Markov chain models, the distribution of functionality in program search spaces, the problem of bloat, the applicability of the no-free-lunch theory to GP, and how we can estimate the difficulty of problems before actually running the system. We then look at how each of these areas might develop in the next decade, considering also new possible avenues for theory, the challenges ahead and the open issues.

Keywords

Genetic programming Theory Challenges Open problems 

Notes

Acknowledgments

The authors would like to thank Julian Miller and the referees of this paper for their extremely useful feedback. Lee Spector is also gratefully thanked.

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Riccardo Poli
    • 1
  • Leonardo Vanneschi
    • 2
  • William B. Langdon
    • 3
  • Nicholas Freitag McPhee
    • 4
  1. 1.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK
  2. 2.Department of Informatics, Systems and Communication (D.I.S.Co.)University of Milano-BicoccaMilanItaly
  3. 3.Department of Computer ScienceKing’s College LondonLondonUK
  4. 4.Division of Science and MathematicsUniversity of Minnesota MorrisMorrisUSA

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