Natural Computing

, Volume 7, Issue 1, pp 21–43 | Cite as

Mapping non-conventional extensions of genetic programming

  • William B. LangdonEmail author
  • Riccardo Poli


Conventional genetic programming research excludes memory and iteration. We have begun an extensive analysis of the space through which GP or other unconventional AI approaches search and extend it to consider explicit program stop instructions (T8), including Markov analysis and any time models (T7). We report halting probability, run time and functionality (including entropy of binary functions) of both halting and anytime programs. Irreversible Turing complete program fitness landscapes, even with halt, scale poorly however loops lock-in variation allowing more interesting functions.


Turing complete Markov analysis of program search spaces Program termination Any time computation Entropy and irreversible loss of information Program convergence Halting probability genetic algorithms Genetic programming 



We would like to thank Dagstuhl Seminar 06061.


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Copyright information

© Springer Science+Business Media, Inc. 2007

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of EssexColchesterUK
  2. 2.Department of Computer ScienceUniversity of EssexColchesterUK

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