Faster algorithms for mean-payoff games
| Authors | |
|---|---|
| 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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