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Genetic Programming




Computer programs in GP can be written in a variety of to generate programs that fully exploit the syntax of a given assembly language.

GP is very computationally intensive and so in the 1990s it was mainly used to solve relatively simple problems. However, more recently, thanks to various improvements in GP technology and to the well known , electronic design, game playing, sorting, searching and many more. These results include the replication or infringement of several post-year-2000 inventions, and the production of two patentable new inventions.

Developing a theory for GP has been very difficult and so in the 1990s genetic programming was considered a sort of pariah amongst the various techniques of search. However, after a series of breakthroughs in the early 2000s, the theory of GP has had a formidable and rapid development. So much so that it has been possible to build exact probabilistic models of GP (schema theories and Markov Chain models) and to show that GP is more general than, and in fact includes, Genetic Algorithm s.

Genetic Programming techniques have now been applied to Evolvable Hardware as well as computer programs.

Meta-Genetic Programming is the technique of evolving a genetic programming system using genetic programming itself. Critics have argued that it is theoretically impossible, but more research is needed.


SEE ALSO

Genetic Representation


BIBLIOGRAPHY

  • Banzhaf, W., Nordin, P., Keller, R.E., Francone, F.D. (1998), ''Genetic Programming: An Introduction: On the Automatic Evolution of Computer Programs and Its Applications'', Morgan Kaufmann

  • Cramer, Nichael Lynn (1985), " A representation for the Adaptive Generation of Simple Sequential Programs " in ''Proceedings of an International Conference on Genetic Algorithms and the Applications'', Grefenstette, John J. (ed.), Carnegie Mellon University

  • Koza, J.R. (1990), ''Genetic Programming: A Paradigm for Genetically Breeding Populations of Computer Programs to Solve Problems'', Stanford University Computer Science Department technical report STAN-CS-90-1314 . A thorough report, possibly used as a draft to his 1992 book.

  • Koza, J.R. (1992), ''Genetic Programming: On the Programming of Computers by Means of Natural Selection'', MIT Press

  • Koza, J.R. (1994), ''Genetic Programming II: Automatic Discovery of Reusable Programs'', MIT Press

  • Koza, J.R., Bennett, F.H., Andre, D., and Keane, M.A. (1999), ''Genetic Programming III: Darwinian Invention and Problem Solving'', Morgan Kaufmann

  • Koza, J.R., Keane, M.A., Streeter, M.J., Mydlowec, W., Yu, J., Lanza, G. (2003), ''Genetic Programming IV: Routine Human-Competitive Machine Intelligence'', Kluwer Academic Publishers

  • Langdon, W. B., Poli, R. (2002), ''Foundations of Genetic Programming'', Springer-Verlag

  • Smith, S.F. (1980), ''A Learning System Based on Genetic Adaptive Algorithms'', PhD dissertation (University of Pittsburgh)



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