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The Automatic Acquisition, Evolution and Re-use of Modules in Cartesian Genetic Programming

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JournalIEEE Transactions on Evolutionary Computation
DatePublished - 1 Aug 2008
Issue number4
Volume12
Number of pages21
Pages (from-to)397-417
Original languageEnglish

Abstract

This paper presents a generalization of the graph- based 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 nonmodular method, and the speedup is more pronounced on larger problems. Also, the new modular method performs favorably when compared with other GP methods. Analysis of the evolved modules shows they often produce recognizable functions. Prospects for further improvements to the method are discussed.

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