An analysis of post-selection in automatic tuning
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.
Artificial Intelligence and Robotics | Business | Operations Research, Systems Engineering and Industrial Engineering
Intelligent Systems and Decision Analytics
Proceedings of the 15th annual conference on Genetic and evolutionary computation
City or Country
Yuan, Zhi; Stuetzle, Thomas; De Oca, Marco Montes; and LAU, Hoong Chuin.
An analysis of post-selection in automatic tuning. (2013). Proceedings of the 15th annual conference on Genetic and evolutionary computation. 1557-1564. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/1813
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