Self-Adapting Semantic Sensitivities for Semantic Similarity Based Crossover

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{q.u.nguyen_etal:cec2010,

• author = "Nguyen Quang Uy and Bob McKay and Michael O'Neill and Nguyen Xuan Hoai",
• title = "Self-Adapting Semantic Sensitivities for Semantic Similarity Based Crossover",
• booktitle = "2010 IEEE World Congress on Computational Intelligence",
• pages = "4034--4040",
• year = "2010",
• address = "Barcelona, Spain",
• month = "18-23 " # jul,
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-1-4244-6910-9",
• DOI = "doi:10.1109/CEC.2010.5586052",
• size = "7 pages",
• organization = "IEEE Computational Intelligence Society",
• publisher = "IEEE Press",
• abstract = "This paper presents two methods for self-adapting the semantic sensitivities in a recently proposed semantics-based crossover: Semantic Similarity based Crossover (SSC)[1]. The first self-adaptation method is inspired by a self-adaptive method for controlling mutation step size in Evolutionary Strategies (1/5 rule). The design of the second takes into account more of our previous experimental observations, that SSC works well only when a certain portion of events successfully exchange semantically similar subtrees. These two proposed methods are then tested on a number of real-valued symbolic regression problems, their performance being compared with SSC using predetermined sensitivities and with standard crossover. The results confirm the benefits of the second self-adaption method.",
• notes = "WCCI 2010. Also known as \cite{5586052}",

}

Genetic Programming entries for Quang Uy Nguyen R I (Bob) McKay Michael O'Neill Nguyen Xuan Hoai

Citations