Faster algorithms for mean-payoff games

  • Authors:
  • L. Brim;J. Chaloupka;L. Doyen;R. Gentilini;J. F. Raskin

  • Affiliations:
  • Faculty of Informatics, Masaryk University, Brno, Czech Republic;Faculty of Informatics, Masaryk University, Brno, Czech Republic;Computer Science Department, Université Libre de Bruxelles (U.L.B.), Brussels, Belgium and LSV, ENS Cachan & CNRS, Cachan, France;Computer Science Department, Université Libre de Bruxelles (U.L.B.), Brussels, Belgium and Department of Mathematics and Informatics, University of Perugia, Perugia, Italy;Computer Science Department, Université Libre de Bruxelles (U.L.B.), Brussels, Belgium

  • Venue:
  • Formal Methods in System Design
  • Year:
  • 2011

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Abstract

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.