Genetically breeding populations of computer programs to solve problems in artificial intelligence

Abstract

The authors describe the genetic programming paradigm, which genetically breeds populations of computer programs to solve problems. In genetic programming, the individuals in the population are hierarchical computer programs of various sizes and shapes. Applications to three problems in artificial intelligence are presented. The first problem involves genetically breeding a population of computer programs to allow an 'artificial ant' to traverse an irregular trail. The second problem involves genetically breeding a minimax control strategy in a different game with an independently acting pursuer and evader. The third problem involves genetically breeding a minimax strategy for a player of a simple discrete two-person game represented by a game tree in extensive form.<>