Strategy improvement and randomized subexponential algorithms for stochastic parity games

  • Authors:
  • Krishnendu Chatterjee;Thomas A. Henzinger

  • Affiliations:
  • EECS, Berkeley, UC;EECS, Berkeley, UC

  • Venue:
  • STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
  • Year:
  • 2006

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Abstract

A stochastic graph game is played by two players on a game graph with probabilistic transitions. We consider stochastic graph games with ω-regular winning conditions specified as parity objectives. These games lie in NP ∩ coNP. We present a strategy improvement algorithm for stochastic parity games; this is the first non-brute-force algorithm for solving these games. From the strategy improvement algorithm we obtain a randomized subexponential-time algorithm to solve such games.