- author = "Nguyen Quang Uy and Michael O'Neill and Xuan Hoai Nguyen and Bob McKay and Edgar Galvan Lopez",
- title = "Semantic Similarity based Crossover in GP: The case for Real-valued Function Regression",
- booktitle = "9th International Conference, Evolution Artificielle, EA 2009",
- year = "2009",
- editor = "Pierre Collet and Nicolas Monmarche and Pierrick Legrand and Marc Schoenauer and Evelyne Lutton",
- volume = "5975",
- series = "Lecture Notes in Computer Science",
- pages = "170--181",
- address = "Strasbourg, France",
- month = oct # " 26-28",
- publisher = "Springer",
- note = "Revised Selected Papers",
- keywords = "genetic algorithms, genetic programming",
- isbn13 = "978-3-642-14155-3",
-
DOI = "
doi:10.1007/978-3-642-14156-0_15",
- size = "12 pages",
- abstract = "In this paper we propose a new method for implementing the crossover operator in Genetic Programming (GP) called Semantic Similarity based Crossover (SSC). This new operator is inspired by Semantic Aware Crossover (SAC) [20]. SSC extends SAC by adding semantics to control the change of the semantics of the individuals during the evolutionary process. The new crossover operator is then tested on a family of symbolic regression problems and compared with SAC as well as Standard Crossover (SC). The results from the experiments show that the change of the semantics (fitness) in the new SSC is smoother compared to SAC and SC. This leads to performance improvement in terms of percentage of successful runs and mean best fitness.",
-
notes = "EA'09 Published 2010
See use of family name (Nguyen) in PhD thesis \cite{Quang_Uy_Nguyen:thesis} Firstnames: Uy Quang
Natural Computing Research & Applications Group, University College Dublin, Ireland
School of Computer Science and Engineering, Seoul National University, Korea",
