Solving the Unknown Complexity Formula Problem with Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8194

@InProceedings{conf/iwann/BatistaSSLR13,

• author = "Rayco Batista and Eduardo Segredo and Carlos Segura and Coromoto Leon and Casiano Rodriguez",
• title = "Solving the Unknown Complexity Formula Problem with Genetic Programming",
• bibdate = "2013-06-25",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/iwann/iwann2013-1.html#BatistaSSLR13",
• booktitle = "Advances in Computational Intelligence - 12th International Work-Conference on Artificial Neural Networks, {IWANN} 2013, Puerto de la Cruz, Tenerife, Spain, June 12-14, 2013, Proceedings, Part {I}",
• publisher = "Springer",
• year = "2013",
• volume = "7902",
• editor = "Ignacio Rojas and Gonzalo Joya Caparr{\'o}s and Joan Cabestany",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-38678-7",
• pages = "232--240",
• series = "Lecture Notes in Computer Science",
• URL = "http://dx.doi.org/10.1007/978-3-642-38679-4",
• DOI = "doi:10.1007/978-3-642-38679-4_22",
• abstract = "The Unknown Complexity Formula Problem (ucfp) is a particular case of the symbolic regression problem in which an analytical complexity formula that fits with data obtained by multiple executions of certain algorithm must be given. In this work, a set of modifications has been added to the standard Genetic Programming (GP) algorithm to deal with the ucfp. This algorithm has been applied to a set of well-known benchmark functions of the symbolic regression problem. Moreover, a real case of the ucfp has been tackled. Experimental evaluation has demonstrated the good behaviour of the proposed approach in obtaining high quality solutions, even for a real instance of the ucfp. Finally, it is worth pointing out that the best published results for the majority of benchmark functions have been improved.",

}

Genetic Programming entries for Rayco Batista Eduardo Segredo Carlos Segura Gonzalez Coromoto Leon Casiano Rodriguez

Citations