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Publication details
Faster algorithms for mean-payoff games
Authors | |
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Year of publication | 2011 |
Type | Article in Periodical |
Magazine / Source | Formal Methods in System Design |
MU Faculty or unit | |
Citation | |
Doi | http://dx.doi.org/10.1007/s10703-010-0105-x |
Field | Informatics |
Keywords | Mean payoff objectives; Algorithms and complexity upper bounds |
Description | In this paper, we study algorithmic problems for quantitative models that are motivated by the applications in modeling embedded systems. We consider two-player games played on a weighted graph with mean-payoff objective and with energy constraints. We present a new pseudopolynomial algorithm for solving such games, improving the best known worst-case complexity for pseudopolynomial mean-payoff algorithms. Our algorithm can also be combined with the procedure by Andersson and Vorobyov to obtain a randomized algorithm with currently the best expected time complexity. The proposed solution relies on a simple fixpoint iteration to solve the log-space equivalent problem of deciding the winner of energy games. Our results imply also that energy games and mean-payoff games can be reduced to safety games in pseudopolynomial time. |
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