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Tree-Structure-Aware Genetic Operators in Genetic Programming
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 Title & Authors
Tree-Structure-Aware Genetic Operators in Genetic Programming
Seo, Kisung; Pang, Chulhyuk;
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 Abstract
In this paper, we suggest tree-structure-aware GP (Genetic Programming) operators that heed tree distributions in structure space and their possible structural difficulties. The main idea of the proposed GP operators is to place the generated offspring of crossover and/or mutation in a specified region of tree structure space insofar as possible by biasing the tree structures of the altered subtrees, taking into account the observation that most solutions are found in that region. To demonstrate the effectiveness of the proposed approach, experiments on the binomial-3 regression, multiplexor and even parity problems are performed. The results show that the results using the proposed tree-structure-aware operators are superior to the results of standard GP for all three test problems in both success rate and number of evaluations.
 Keywords
Genetic programming;Genetic operators;Crossover;Balanced tree structures;
 Language
English
 Cited by
1.
ADF를 사용한 유전프로그래밍 기반 비선형 회귀분석 기법 개선 및 풍속 예보 보정 응용,오승철;서기성;

전기학회논문지, 2015. vol.64. 12, pp.1748-1755 crossref(new window)
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