Algorithm configuration: Learning policies for the quick termination of poor performers

Abstract

© 2019, Springer Nature Switzerland AG. One way to speed up the algorithm configuration task is to use short runs instead of long runs as much as possible, but without discarding the configurations that eventually do well on the long runs. We consider the problem of selecting the top performing configurations of Conditional Markov Chain Search (CMCS), a general algorithm schema that includes, for example, VNS. We investigate how the structure of performance on short tests links with those on long tests, showing that significant differences arise between test domains. We propose a “performance envelope” method to exploit the links; that learns when runs should be terminated, but that automatically adapts to the domain.

Citation

Karapetyan, D., Parkes, A. J., & Stützle, T. (2019). Algorithm configuration: Learning policies for the quick termination of poor performers. . https://doi.org/10.1007/978-3-030-05348-2_20

• Conference Name: LION 12 Learning and Intelligent Optimization Conference
• Start Date: Jun 10, 2018
• End Date: Jun 15, 2018
• Acceptance Date: May 14, 2018
• Online Publication Date: Dec 31, 2018
• Publication Date: Jan 1, 2019
• Deposit Date: Mar 17, 2019
• Publicly Available Date: Mar 18, 2019
• Journal: Lecture Notes in Computer Science; Learning and Intelligent Optimization
• Electronic ISSN: 1611-3349
• Publisher: Springer Verlag
• Volume: 11353 LNCS
• Pages: 220-224
• Series Title: Lecture notes in computer science
• Series Number: 11353
• Series ISSN: 0302-9743
• ISBN: 9783030053475
• DOI: https://doi.org/10.1007/978-3-030-05348-2_20
• Public URL: https://nottingham-repository.worktribe.com/output/1659549
• Publisher URL: https://link.springer.com/chapter/10.1007%2F978-3-030-05348-2_20
• Additional Information: Conference Acronym: LION 12; Conference Name: International Conference on Learning and Intelligent Optimization; Conference City: Kalamata; Conference Country: Greece; Conference Year: 2018; Conference Start Date: 10 June 2018; Conference End Date: 15 June 2018; Conference Number: 12; Conference ID: lion2018; Conference URL: http://www.caopt.com/LION12/