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The Automatic Acquisition, Evolution and Reuse of Modules in Cartesian Genetic Programming
2008
IEEE Transactions on Evolutionary Computation
This paper presents a generalization of the graphbased genetic programming (GP) technique known as Cartesian genetic programming (CGP). We have extended CGP by utilizing automatic module acquisition, evolution, and reuse. To benchmark the new technique, we have tested it on: various digital circuit problems, two symbolic regression problems, the lawnmower problem, and the hierarchical if-and-only-if problem. The results show the new modular method evolves solutions quicker than the original
doi:10.1109/tevc.2007.903549
fatcat:vdjbnadxy5e4jkww66ptlizlcu