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:
“Man is not merely the sum of his masks. Behind the shifting face of personality is a hard nugget of self, a genetic gift.... The self is malleable but elastic, snapping back to its original shape like a rubber band. Mental illness is no myth, as some have claimed. It is a disturbance in our sense of possession of a stable inner self that survives its personae.”
—Camille Paglia (b. 1947)
“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.”
—Melinda M. Marshall (20th century)