An algorithm for probabilistic alternating simulation

  • Authors:
  • Chenyi Zhang;Jun Pang

  • Affiliations:
  • University of Queensland, Brisbane, Australia;University of Luxembourg, Luxembourg

  • Venue:
  • SOFSEM'12 Proceedings of the 38th international conference on Current Trends in Theory and Practice of Computer Science
  • Year:
  • 2012

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Abstract

In probabilistic game structures, probabilistic alternating simulation (PA-simulation) relations preserve formulas defined in probabilistic alternating-time temporal logic with respect to the behaviour of a subset of players. We propose a partition based algorithm for computing the largest PA-simulation. It is to our knowledge the first such algorithm that works in polynomial time. Our solution extends the generalised coarsest partition problem (GCPP) to a game-based setting with mixed strategies. The algorithm has higher complexities than those in the literature for non-probabilistic simulation and probabilistic simulation without mixed actions, but slightly improves the existing result for computing probabilistic simulation with respect to mixed actions.