Theoretical results in genetic programming: The next ten years?

Riccardo Poli, Leonardo Vanneschi, William B. Langdon, Nicholas Freitag McPhee

    Research output: Contribution to journalArticlepeer-review

    36 Scopus citations

    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.

    Original languageEnglish (US)
    Pages (from-to)285-320
    Number of pages36
    JournalGenetic Programming and Evolvable Machines
    Volume11
    Issue number3-4
    DOIs
    StatePublished - Sep 2010

    Keywords

    • Challenges
    • Genetic programming
    • Open problems
    • Theory

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