Is Ambiguity Useful or Problematic for Grammar Guided Genetic Programming?

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@InProceedings{hoai:2002:SEAL,

• author = "Nguyen Xuan Hoai and Yin Shan and Robert Ian McKay",
• title = "Is Ambiguity Useful or Problematic for Grammar Guided Genetic Programming?",
• booktitle = "Procedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL'02)",
• year = "2002",
• editor = "Lipo Wang and Kay Chen Tan and Takeshi Furuhashi and Jong-Hwan Kim and Xin Yao",
• pages = "449--454",
• address = "Orchid Country Club, Singapore",
• month = "18-22 " # nov,
• keywords = "genetic algorithms, genetic programming",
• ISBN = "981-04-7522-5",
• URL = "http://www.cs.adfa.edu.au/~shanyin/publications/ambiguity.pdf",
• URL = "http://citeseer.ist.psu.edu/545311.html",
• URL = "http://sc.snu.ac.kr/PAPERS/ambiguity.pdf",
• abstract = "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.",
• notes = "SEAL 2002 see http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.200.6410&rep=rep1&type=pdf",
• notes = "Refereed International Conference Papers",

}

Genetic Programming entries for Nguyen Xuan Hoai Yin Shan R I (Bob) McKay

Citations