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Improved Bounds for Strategy Improvement Algorithms for Energy Games

  • Max Planck Institute for Informatics

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

Abstract

Strategy improvement is a natural and well-studied family of algorithms for solving various classes of stochastic and deterministic graph games. We present an improved upper bound of O(n2n) on the number of iterations performed by the most natural, and most greedy, variant of the algorithm when applied to n-vertex Energy Games. We also obtain a similar upper bound of O(poly(n) · 2n) on the expected number of iterations performed by Random-Edge, one of the most natural randomized variants of the algorithm. To the best of our knowledge, these are the first bounds for natural strategy-improvement algorithms on non-binary energy games that beat the trivial nn = 2n log n bound obtained by enumerating all strategies. The proof is based on a new adaptation of the layering technique of [Dorfman, Kaplan, Zwick, ICALP 2019].

Original languageEnglish
Title of host publication34th Annual European Symposium on Algorithms, ESA 2026
EditorsPhilip Bille, Seth Pettie, Sabine Storand
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959774451
DOIs
StatePublished - 25 Aug 2026
Event34th Annual European Symposium on Algorithms, ESA 2026 - L�Aquila, Italy
Duration: 31 Aug 2026 → 4 Sep 2026

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
Volume388
ISSN (Print)1868-8969

Conference

Conference34th Annual European Symposium on Algorithms, ESA 2026
Country/TerritoryItaly
CityL�Aquila
Period31/08/26 → 4/09/26

Funding

FundersFunder number
Blavatnik Family Foundation
Israel Science Foundation2854/20, 1156-23

    Keywords

    • Energy Games
    • Graph Games
    • Strategy improvement

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