Using Software Engineering Knowledge to Drive Genetic Program Design Using Cultural Algorithms Exploiting the Synergy of Software Engineering Knowledge in Evolutionary Design

Created by W.Langdon from gp-bibliography.bib Revision:1.8098

@InCollection{ostrowski:2003:GPTP,

• author = "David A. Ostrowski and Robert G. Reynolds",
• title = "Using Software Engineering Knowledge to Drive Genetic Program Design Using Cultural Algorithms Exploiting the Synergy of Software Engineering Knowledge in Evolutionary Design",
• booktitle = "Genetic Programming Theory and Practice",
• publisher = "Kluwer",
• year = "2003",
• editor = "Rick L. Riolo and Bill Worzel",
• chapter = "5",
• pages = "63--80",
• keywords = "genetic algorithms, genetic programming, cultural algorithms, Hybrid genetic programming environments, agent-based modeling, OEM strategy evolution, black box testing, white box testing",
• ISBN = "1-4020-7581-2",
• URL = "http://www.springer.com/computer/ai/book/978-1-4020-7581-0",
• DOI = "doi:10.1007/978-1-4419-8983-3_5",
• abstract = "In this paper we use Cultural Algorithms as a framework in which to embed a white and black box testing strategy for designing and testing large-scale GP programs. The model consists of two populations, one supports white box testing of a Genetic Programming system and the other supports black box testing. The two populations communicate by sending information to a shared belief space. This allows a potential synergy between the two activities. Next, we exploit this synergy in order to evolve an OEM pricing strategy in a complex agent-based market environment. The new pricing strategy generated over $2 million dollars in revenue during the assessment period and outperformed the previous optimal strategy.",
• notes = "Part of \cite{RioloWorzel:2003}",

}

Genetic Programming entries for David A Ostrowski Robert G Reynolds

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