Algorithm selection in optimization and application to angry birds

Shahaf S. Shperberg, Solomon Eyal Shimony, Avinoam Yehezkel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 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 languageEnglish
Title of host publicationProceedings of the 29th International Conference on Automated Planning and Scheduling, ICAPS 2019
EditorsJ. Benton, Nir Lipovetzky, Eva Onaindia, David E. Smith, Siddharth Srivastava
PublisherAAAI press
Pages437-445
Number of pages9
ISBN (Electronic)9781577358077
StatePublished - 1 Jan 2019
Event29th International Conference on Automated Planning and Scheduling, ICAPS 2019 - Berkeley, United States
Duration: 11 Jul 201915 Jul 2019

Publication series

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

Conference

Conference29th International Conference on Automated Planning and Scheduling, ICAPS 2019
Country/TerritoryUnited States
CityBerkeley
Period11/07/1915/07/19

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management

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