Extending the ``Open-Closed Principle'' to Automated Algorithm Configuration

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@Article{Swan:2019:EC,

• author = "Jerry Swan and Steven Adriaensen and Adam D. Barwell and Kevin Hammond and David R. White",
• title = "Extending the {``}Open-Closed Principle{''} to Automated Algorithm Configuration",
• journal = "Evolutionary Computation",
• year = "2019",
• volume = "27",
• number = "1",
• pages = "173--193",
• month = "Spring",
• keywords = "genetic algorithms, genetic programming, Automated Design of Algorithms, Automatic Programming, Programming by Optimization, Metaheuristics, Functional Programming, Ant Programming, SBSE, Search Based Software Engineering, Systems Self Assembly",
• ISSN = "1063-6560",
• DOI = "doi:10.1162/evco_a_00245",
• size = "20 pages",
• abstract = "Metaheuristics are an effective and diverse class of optimization algorithms: a means of obtaining solutions of acceptable quality for otherwise intractable problems. The selection, construction, and configuration of a metaheuristic for a given problem has historically been a manually intensive process based on experience, experimentation, and reasoning by metaphor. More recently, there has been interest in automating the process of algorithm configuration. In this paper, we identify shared state as an inhibitor of progress for such automation. To solve this problem, we introduce the Automated Open Closed Principle (AOCP), which stipulates design requirements for unobtrusive reuse of algorithm frameworks and automated assembly of algorithms from an extensible palette of components. We demonstrate how the AOCP enables a greater degree of automation than previously possible via an example implementation.",
• notes = "Is this GP?",

}

Genetic Programming entries for Jerry Swan Steven Adriaensen Adam D Barwell Kevin Hammond David Robert White

Citations