John Koza, a Stanford University researcher, developed genetic programming as a method to evolve computer programs by simulating the natural selection process. In this approach, a population of computer programs, composed of primitive functions and terminals, is evolved to solve a given problem. Each program's fitness is determined by its effectiveness in solving the problem. A few programs with high fitness are selected for reproduction, while many participate in a recombination operation called crossover. By iterating this process over multiple generations, the structure of a computer program that effectively solves the problem can emerge.
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