Assessing the Effectiveness of Incorporating Knowledge in an Evolutionary Concept Learner

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

@InProceedings{eurogp:Divina05,

• author = "Federico Divina",
• editor = "Maarten Keijzer and Andrea Tettamanzi and Pierre Collet and Jano I. {van Hemert} and Marco Tomassini",
• title = "Assessing the Effectiveness of Incorporating Knowledge in an Evolutionary Concept Learner",
• booktitle = "Proceedings of the 8th European Conference on Genetic Programming",
• publisher = "Springer",
• series = "Lecture Notes in Computer Science",
• volume = "3447",
• year = "2005",
• address = "Lausanne, Switzerland",
• month = "30 " # mar # " - 1 " # apr,
• organisation = "EvoNet",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "3-540-25436-6",
• pages = "13--24",
• URL = "http://www.cs.vu.nl/~divina/Publications/EuroGP-divina.pdf",
• DOI = "doi:10.1007/978-3-540-31989-4_2",
• DOI = "doi:10.1007/b107383",
• bibsource = "DBLP, http://dblp.uni-trier.de",
• size = "12 pages",
• abstract = "Classical methods for Inductive Concept Learning (ICL) rely mostly on using specific search strategies, as hill climbing and inverse resolution. These strategies have a great exploitation power, but run the risk of being incapable of escaping from local optima. An alternative approach to ICL is represented by Evolutionary Algorithms (EAs). EAs have a great exploration power, thus they have the capability of escaping from local optima, but their exploitation power is rather poor. These observations suggest that the two approaches are applicable to partly complementary classes of learning problems. More important, they indicate that a system incorporating features from both approaches could benefit from the complementary qualities of the approaches. In this paper we experimentally validate this statement. To this end, we incorporate different search strategies in a framework based on EAs for ICL. Results of experiments show that incorporating standard search strategies helps the EAs in achieving better results.",
• notes = "Part of \cite{keijzer:2005:GP} EuroGP'2005 held in conjunction with EvoCOP2005 and EvoWorkshops2005",

}

Genetic Programming entries for Federico Divina

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