Algorithm selection in optimization and application to angry birds

Shahaf S. Shperberg; Solomon Eyal Shimony; Avinoam Yehezkel

doi:10.1609/icaps.v29i1.3508

Algorithm selection in optimization and application to angry birds

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

Consider the MaxScore algorithm selection problem: given some optimization problem instances, a set of algorithms that solve them, and a time limit, what is the optimal policy for selecting (algorithm, instance) runs so as to maximize the sum of solution qualities for all problem instances? We analyze the computational complexity of restrictions of MaxScore (NP-hard), and provide a dynamic programming approximation algorithm. This algorithm, as well as new greedy algorithms, are evaluated empirically on data from agent runs on Angry Birds problem instances. Results show a significant improvement over a hyper-agent greedy scheme from related work.

Original language	English
Title of host publication	Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019
Editors	J. Benton, Nir Lipovetzky, Eva Onaindia, David E. Smith, Siddharth Srivastava
Publisher	Association for the Advancement of Artificial Intelligence
Pages	437-445
Number of pages	9
ISBN (Electronic)	9781577358077
DOIs	https://doi.org/10.1609/icaps.v29i1.3508
State	Published - 1 Jan 2019
Event	29th International Conference on Automated Planning and Scheduling, ICAPS 2019 - Berkeley, United States Duration: 11 Jul 2019 → 15 Jul 2019

Publication series

Name	Proceedings International Conference on Automated Planning and Scheduling, ICAPS
ISSN (Print)	2334-0835
ISSN (Electronic)	2334-0843

Conference

Conference	29th International Conference on Automated Planning and Scheduling, ICAPS 2019
Country/Territory	United States
City	Berkeley
Period	11/07/19 → 15/07/19

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Information Systems and Management

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10.1609/icaps.v29i1.3508

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Shperberg, S. S., Shimony, S. E., & Yehezkel, A. (2019). Algorithm selection in optimization and application to angry birds. In J. Benton, N. Lipovetzky, E. Onaindia, D. E. Smith, & S. Srivastava (Eds.), Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019 (pp. 437-445). (Proceedings International Conference on Automated Planning and Scheduling, ICAPS). Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/icaps.v29i1.3508

Shperberg, Shahaf S. ; Shimony, Solomon Eyal ; Yehezkel, Avinoam. / Algorithm selection in optimization and application to angry birds. Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019. editor / J. Benton ; Nir Lipovetzky ; Eva Onaindia ; David E. Smith ; Siddharth Srivastava. Association for the Advancement of Artificial Intelligence, 2019. pp. 437-445 (Proceedings International Conference on Automated Planning and Scheduling, ICAPS).

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title = "Algorithm selection in optimization and application to angry birds",

abstract = "Consider the MaxScore algorithm selection problem: given some optimization problem instances, a set of algorithms that solve them, and a time limit, what is the optimal policy for selecting (algorithm, instance) runs so as to maximize the sum of solution qualities for all problem instances? We analyze the computational complexity of restrictions of MaxScore (NP-hard), and provide a dynamic programming approximation algorithm. This algorithm, as well as new greedy algorithms, are evaluated empirically on data from agent runs on Angry Birds problem instances. Results show a significant improvement over a hyper-agent greedy scheme from related work.",

author = "Shperberg, \{Shahaf S.\} and Shimony, \{Solomon Eyal\} and Avinoam Yehezkel",

note = "Publisher Copyright: {\textcopyright} 2019, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 29th International Conference on Automated Planning and Scheduling, ICAPS 2019 ; Conference date: 11-07-2019 Through 15-07-2019",

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doi = "10.1609/icaps.v29i1.3508",

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series = "Proceedings International Conference on Automated Planning and Scheduling, ICAPS",

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Shperberg, SS , Shimony, SE & Yehezkel, A 2019, Algorithm selection in optimization and application to angry birds. in J Benton, N Lipovetzky, E Onaindia, DE Smith & S Srivastava (eds), Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019. Proceedings International Conference on Automated Planning and Scheduling, ICAPS, Association for the Advancement of Artificial Intelligence, pp. 437-445, 29th International Conference on Automated Planning and Scheduling, ICAPS 2019, Berkeley, United States, 11/07/19. https://doi.org/10.1609/icaps.v29i1.3508

Algorithm selection in optimization and application to angry birds. / Shperberg, Shahaf S.; Shimony, Solomon Eyal; Yehezkel, Avinoam.
Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019. ed. / J. Benton; Nir Lipovetzky; Eva Onaindia; David E. Smith; Siddharth Srivastava. Association for the Advancement of Artificial Intelligence, 2019. p. 437-445 (Proceedings International Conference on Automated Planning and Scheduling, ICAPS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Consider the MaxScore algorithm selection problem: given some optimization problem instances, a set of algorithms that solve them, and a time limit, what is the optimal policy for selecting (algorithm, instance) runs so as to maximize the sum of solution qualities for all problem instances? We analyze the computational complexity of restrictions of MaxScore (NP-hard), and provide a dynamic programming approximation algorithm. This algorithm, as well as new greedy algorithms, are evaluated empirically on data from agent runs on Angry Birds problem instances. Results show a significant improvement over a hyper-agent greedy scheme from related work.

AB - Consider the MaxScore algorithm selection problem: given some optimization problem instances, a set of algorithms that solve them, and a time limit, what is the optimal policy for selecting (algorithm, instance) runs so as to maximize the sum of solution qualities for all problem instances? We analyze the computational complexity of restrictions of MaxScore (NP-hard), and provide a dynamic programming approximation algorithm. This algorithm, as well as new greedy algorithms, are evaluated empirically on data from agent runs on Angry Birds problem instances. Results show a significant improvement over a hyper-agent greedy scheme from related work.

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Shperberg SS , Shimony SE, Yehezkel A. Algorithm selection in optimization and application to angry birds. In Benton J, Lipovetzky N, Onaindia E, Smith DE, Srivastava S, editors, Proceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019. Association for the Advancement of Artificial Intelligence. 2019. p. 437-445. (Proceedings International Conference on Automated Planning and Scheduling, ICAPS). doi: 10.1609/icaps.v29i1.3508

Algorithm selection in optimization and application to angry birds

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