Genetic programming is a subfield of evolutionary computation introduced by John Koza in his 1992 book Genetic Programming: On the Programming of Computers by Means of Natural Selection. It is a method used to allow a computer programs to be evolved according to some user-defined goal. It uses evolutionary patterns, using crossover, selection, replication and mutations to evolve the programs which are usually represented by LISP expressions. In order to work effectively requires an appropriate selection of operators and variables.
Unfortunately, due to the lack of solid theory regarding the performance of genetic algorithms 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.
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