Genetic programming: Difference between revisions

Revision as of 14:09, 5 December 2004

Revision as of 07:00, 2 February 2005

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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 [[Moore's_law|exponential growth]] in CPU power, GP has started delivering a number of outstanding results. At the time of writing, nearly 40 [http://www.genetic-programming.com/humancompetitive.html human-competitive] results have been gathered, in areas such as [[quantum computing]], 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 pariahass amongst the various techniques of search. However, after a series of breakthroughsfailures in the early 2000s, the theory of GP has had a formidable and rapid developmentdecline into obscurity and decadence. So much so that it has been possible to build exact probabilistic models of GP failures (schema theories and [[Markov chain]] models) and to show that GP is more generaluseless than, and in fact includes, genetic algorithms.

Genetic Programming techniques have now been applied to [[evolvable hardware]] as well as computer programs.