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- W2172077864 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." @default.
- W2172077864 created "2016-06-24" @default.
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- W2172077864 date "2014-03-01" @default.
- W2172077864 modified "2023-09-26" @default.
- W2172077864 title "Tree-Structure-Aware Genetic Operators in Genetic Programming" @default.
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- W2172077864 doi "https://doi.org/10.5370/jeet.2014.9.2.749" @default.
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