Rule-based Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@InProceedings{WZG2007DGPFi,

• author = "Thomas Weise and Michael Zapf and Kurt Geihs",
• title = "Rule-based Genetic Programming",
• booktitle = "Proceedings of BIONETICS 2007, 2nd International Conference on Bio-Inspired Models of Network, Information, and Computing Systems",
• publisher = "Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (ICST), IEEE, ACM",
• year = "2007",
• pages = "8--15",
• month = "10-12 " # dec,
• affiliation = "University of Kassel",
• address = "Radisson SAS Beke Hotel, 43. Terez krt., Budapest H-1067, Hungary",
• keywords = "genetic algorithms, genetic programming, Rule-based Genetic Programming, GP, Distributed Systems, Critical Section, Epistasis, Neutrality, Learning Classifier Systems",
• isbn13 = "978-963-9799-05-9",
• language = "en",
• URL = "http://www.it-weise.de/documents/files/WZG2007RBGP.pdf",
• DOI = "doi:10.1109/BIMNICS.2007.4610073",
• abstract = "In this paper we introduce a new approach for Genetic Programming, called rule-based Genetic Programming, or RBGP in short. A program evolved in the RBGP syntax is a list of rules. Each rule consists of two conditions, combined with a logical operator, and an action part. Such rules are independent from each other in terms of position (mostly) and cardinality (always). This reduces the epistasis drastically and hence, the genetic reproduction operations are much more likely to produce good results than in other Genetic Programming methodologies. we apply RBGP to a hard problem in distributed systems. With it, we are able to obtain emergent algorithms for mutual exclusion at a distributed critical section.",
• notes = "Also known as \cite{4610073}",

}

Genetic Programming entries for Thomas Weise Michael Zapf Kurt Geihs

Citations