Is Ambiguity Useful or Problematic for Grammar Guided Genetic Programming? a Case Study
نویسندگان
چکیده
In [2] Antonisse made a conjecture that unambiguous grammars are better candidates for grammar-guided genetic learning. In this paper, we empirically show that it is not always the case, especially when the structural ambiguity is boosted by semantic redundancies in the grammar. We also show that the search space (or genotype space) of grammar guided genetic programming (GGGP) is truly tree sets rather than string sets of formalisms.
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