Genetically breeding populations of computer programs to solve problems in artificial intelligence
- 4 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 819-827
- https://doi.org/10.1109/tai.1990.130444
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.<>Keywords
This publication has 2 references indexed in Scilit:
- Genetic breeding of non-linear optimal control strategies for broom balancingPublished by Springer Nature ,1990
- Learning with genetic algorithms: An overviewMachine Learning, 1988