Theoretical results in genetic programming: the next ten years?

Authors:
Riccardo Poli;Leonardo Vanneschi;William B. Langdon;Nicholas Freitag Mcphee
Affiliations:
School of Computer Science and Electronic Engineering, University of Essex, Colchester, UK CO4 3SQ;Department of Informatics, Systems and Communication (D.I.S.Co.), University of Milano-Bicocca, Milan, Italy 336-U14;Department of Computer Science, King's College London, London, UK WC2R 2LS;Division of Science and Mathematics, University of Minnesota Morris, Morris, USA 56267
Venue:
Genetic Programming and Evolvable Machines
Year:
2010

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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.