Evolving genetic programming classifiers with novelty search

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

@Article{Naredo:2016:IS,

• author = "Enrique Naredo and Leonardo Trujillo and Pierrick Legrand and Sara Silva and Luis Munoz",
• title = "Evolving genetic programming classifiers with novelty search",
• journal = "Information Sciences",
• year = "2016",
• volume = "369",
• pages = "347--367",
• month = "10 " # nov,
• keywords = "genetic algorithms, genetic programming, Novelty search, Behaviour-based Search, Supervised classification, Bloat",
• ISSN = "0020-0255",
• URL = "http://www.sciencedirect.com/science/article/pii/S002002551630473X",
• DOI = "doi:10.1016/j.ins.2016.06.044",
• abstract = "Novelty Search (NS) is a unique approach towards search and optimization, where an explicit objective function is replaced by a measure of solution novelty. However, NS has been mostly used in evolutionary robotics while its usefulness in classic machine learning problems has not been explored. This work presents a NS-based genetic programming (GP) algorithm for supervised classification. Results show that NS can solve real-world classification tasks, the algorithm is validated on real-world benchmarks for binary and multiclass problems. These results are made possible by using a domain-specific behaviour descriptor. Moreover, two new versions of the NS algorithm are proposed, Probabilistic NS (PNS) and a variant of Minimal Criteria NS (MCNS). The former models the behavior of each solution as a random vector and eliminates all of the original NS parameters while reducing the computational overhead of the NS algorithm. The latter uses a standard objective function to constrain and bias the search towards high performance solutions. The paper also discusses the effects of NS on GP search dynamics and code growth. Results show that NS can be used as a realistic alternative for supervised classification, and specifically for binary problems the NS algorithm exhibits an implicit bloat control ability.",

}

Genetic Programming entries for Enrique Naredo Leonardo Trujillo Pierrick Legrand Sara Silva Luis Munoz Delgado

Citations