Investigating the Baldwin Effect on Cartesian Genetic Programming Efficiency

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Khatir:2008:cec,

• author = "Mehrdad Khatir and Amir Hossein Jahangir and Hamid Beigy",
• title = "Investigating the Baldwin Effect on Cartesian Genetic Programming Efficiency",
• booktitle = "2008 IEEE World Congress on Computational Intelligence",
• year = "2008",
• editor = "Jun Wang",
• pages = "2360--2364",
• address = "Hong Kong",
• month = "1-6 " # jun,
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• isbn13 = "978-1-4244-1823-7",
• file = "EC0549.pdf",
• DOI = "doi:10.1109/CEC.2008.4631113",
• abstract = "Cartesian Genetic Programming (CGP) has an unusual genotype representation which makes it more efficient than Genetic programming (GP) in digital circuit design problem. However, to the best of our knowledge, all methods used in evolutionary design of digital circuits deal with rugged, complex search space, which results in long running time to obtain successful evolution. Therefore, employing a method to guide evolution in these spaces can facilitate achieving more reasonable results. It has been claimed that a two-step evolutionary scenario caused by benefit and cost of learning called Baldwin effect can guide evolution in the biology and artificial life. Therefore, we have been motivated to examine this effect on CGP. We observe using this scenario the success rate and evolution time of CGP improves dramatically especially when size of chromosomes increases.",
• keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, Baldwin Effect, Phenotypic Plasticity, Digital Circuit, Reinforcement Learning.",
• notes = "WCCI 2008 - A joint meeting of the IEEE, the INNS, the EPS and the IET.",

}

Genetic Programming entries for Mehrdad Khatir Amir Hossein Jahangir Hamid Beigy

Citations