Genetic Programming
In artificial intelligence, genetic programming (GP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms (GA) where each individual is a computer program. It is a machine learning technique used to optimize a population of computer programs according to a fitness landscape determined by a program's ability to perform a given computational task.
Read more about Genetic Programming: History, Program Representation, Other Approaches, MOSES, Meta-Genetic Programming, Implementations
Famous quotes containing the words genetic and/or programming:
“Nature, we are starting to realize, is every bit as important as nurture. Genetic influences, brain chemistry, and neurological development contribute strongly to who we are as children and what we become as adults. For example, tendencies to excessive worrying or timidity, leadership qualities, risk taking, obedience to authority, all appear to have a constitutional aspect.”
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“If there is a price to pay for the privilege of spending the early years of child rearing in the driver’s seat, it is our reluctance, our inability, to tolerate being demoted to the backseat. Spurred by our success in programming our children during the preschool years, we may find it difficult to forgo in later states the level of control that once afforded us so much satisfaction.”
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