mGGA: The meta-Grammar Genetic Algorithm

نویسندگان

  • Michael O'Neill
  • Anthony Brabazon
چکیده

A novel Grammatical Genetic Algorithm, the meta-Grammar Genetic Algorithm (mGGA) is presented. The mGGA borrows a grammatical representation and the ideas of modularity and reuse from Genetic Programming, and in particular an evolvable grammar representation from Grammatical Evolution by Grammatical Evolution. We demonstrate its application to a number of benchmark problems where significant performance gains are achieved when compared to static grammars.

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تاریخ انتشار 2005