Conference Proceeding Article
Automated algorithm configuration methods have proven to be instrumental in deriving high-performing algorithms and such methods are increasingly often used to configure evolutionary algorithms. One major challenge in devising automatic algorithm configuration techniques is to handle the inherent stochasticity in the configuration problems. This article analyses a post-selection mechanism that can also be used for this task. The central idea of the post-selection mechanism is to generate in a first phase a set of high-quality candidate algorithm configurations and then to select in a second phase from this candidate set the (statistically) best configuration. Our analysis of this mechanism indicates its high potential and suggests that it may be helpful to improve automatic algorithm configuration methods.
Automatic algorithm configuration, Post-selection, Search
Artificial Intelligence and Robotics | Computer Sciences | Numerical Analysis and Scientific Computing
Intelligent Systems and Decision Analytics
GECCO'13: Proceedings of the 2013 Genetic and Evolutionary Computation Conference: July 6-10, 2013, Amsterdam
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YUAN, Zhi; St\303\274tzle, Thomas; Montes De Oca, Marco A.; LAU, Hoong Chuin; and Birattari, Mauro.
An analysis of post-selection in automatic configuration. (2013). GECCO'13: Proceedings of the 2013 Genetic and Evolutionary Computation Conference: July 6-10, 2013, Amsterdam. 1557-1564. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3369
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