2026-07-20T01:35:07Z https://drops.dagstuhl.de/oai

oai:drops-oai.dagstuhl.de:10690 2024-03-06T10:46:28Z ddc:004 open_access

A Faster Deterministic Exponential Time Algorithm for Energy Games and Mean Payoff Games (Track B: Automata, Logic, Semantics, and Theory of Programming) Dorfman, Dani Kaplan, Haim Zwick, Uri Energy Games Mean Payoff Games Scaling We present an improved exponential time algorithm for Energy Games, and hence also for Mean Payoff Games. The running time of the new algorithm is O (min(m n W, m n 2^{n/2} log W)), where n is the number of vertices, m is the number of edges, and when the edge weights are integers of absolute value at most W. For small values of W, the algorithm matches the performance of the pseudopolynomial time algorithm of Brim et al. on which it is based. For W >= n2^{n/2}, the new algorithm is faster than the algorithm of Brim et al. and is currently the fastest deterministic algorithm for Energy Games and Mean Payoff Games. The new algorithm is obtained by introducing a technique of forecasting repetitive actions performed by the algorithm of Brim et al., along with the use of an edge-weight scaling technique. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Dani Dorfman and Haim Kaplan and Uri Zwick 2019 Is Part Of LIPIcs, Volume 132, 46th International Colloquium on Automata, Languages, and Programming (ICALP 2019) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/LIPIcs.ICALP.2019.114 urn:nbn:de:0030-drops-106909 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2019.114 eng https://creativecommons.org/licenses/by/3.0/legalcode