Genetic programming: Difference between revisions

Revision as of 12:17, 24 September 2004

Revision as of 02:29, 19 October 2004

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The application of a tree representation (and required genetic operators) for using genetic algorithms to generate programs was first described in 1985 by Cramer. Koza, though he did first explore genetic programming, is indisputably the field's most prolific and persuasive author. Koza and other early GP researchers used the artificial inteligence language [[Lisp_programming_language|Lisp]] to program their GPs.

So far GPs have successfully solved maymany of AI's toy problems, but the method is very computationally intensive, and may not compare favourably where simpler methods, such as [[genetic algorithm]]s or [[random optimisation]] can be used instead. It is possible that some more complex problems may be more amenable to solution using GPs than other optimization methods.

Unfortunately, due to the lack of solid theory regarding the performance of genetic programming vs. traditional search methods (such as [[hill climbing]]), genetic programming remains a sort of pariah amongst the various techniques of search. While genetic programming has achieved results that are as good as and sometimes better than human-generated results, more work needs to be done on the theory in order to bring the technique into more widespread use.