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Extending the ‘Open-Closed Principle’ to automated algorithm configuration

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Paper.pdf (211.3Kb)
Date
04/03/2019
Author
Swan, Jerry
Adriænsen, Stephen
Barwell, Adam David
Hammond, Kevin
White, David
Keywords
Automated design of algorithms
Automatic programming
Programming by optimization
Metaheuristics
Functional programming
Ant programming
Search based software engineering
Systems self assembly
QA75 Electronic computers. Computer science
QA76 Computer software
T-NDAS
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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 unintrusive 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.
Citation
Swan , J , Adriænsen , S , Barwell , A D , Hammond , K & White , D 2019 , ' Extending the ‘Open-Closed Principle’ to automated algorithm configuration ' , Evolutionary Computation , vol. 27 , no. 1 , pp. 173-193 . https://doi.org/10.1162/evco_a_00245
Publication
Evolutionary Computation
Status
Peer reviewed
DOI
https://doi.org/10.1162/evco_a_00245
ISSN
1063-6560
Type
Journal article
Rights
© 2018, Massachusetts Institute of Technology. This work has been made available online in accordance with the publisher's policies. This is the author created accepted version manuscript following peer review and as such may differ slightly from the final published version. The final published version of this work is available at https://doi.org/10.1162/evco_a_00245
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  • University of St Andrews Research
URL
http://eproof.aptaracorp.com/powerproof2/adp.do?aid=7037628478200228772
URI
http://hdl.handle.net/10023/16809

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