Theory of linear and integer programming
Theory of linear and integer programming
Bisimulation through probabilistic testing
Information and Computation
Deciding bisimilarity and similarity for probabilistic processes
Journal of Computer and System Sciences
Communication and Concurrency
Probabilistic simulations for probabilistic processes
Nordic Journal of Computing
Decision Algorithms for Probabilistic Bisimulation
CONCUR '02 Proceedings of the 13th International Conference on Concurrency Theory
It Usually Works: The Temporal Logic of Stochastic Systems
Proceedings of the 7th International Conference on Computer Aided Verification
Quantitative solution of omega-regular games
Journal of Computer and System Sciences - STOC 2001
Approximate Reasoning for Real-Time Probabilistic Processes
QEST '04 Proceedings of the The Quantitative Evaluation of Systems, First International Conference
LICS '07 Proceedings of the 22nd Annual IEEE Symposium on Logic in Computer Science
Approximate Analysis of Probabilistic Processes: Logic, Simulation and Games
QEST '08 Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems
Metrics for finite Markov decision processes
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Labelled Markov Processes
Discounting the future in systems theory
ICALP'03 Proceedings of the 30th international conference on Automata, languages and programming
On the Complexity of Nash Equilibria and Other Fixed Points
SIAM Journal on Computing
On the complexity of computing probabilistic bisimilarity
FOSSACS'12 Proceedings of the 15th international conference on Foundations of Software Science and Computational Structures
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In this paper we study the complexity of computing the game bisimulation metric defined by de Alfaro et al. on Markov Decision Processes. It is proved by de Alfaro et al. that the undiscounted version of the metric is characterized by a quantitative game μ-calculus defined by de Alfaro and Majumdar, which can express reachability and ω-regular specifications. And by Chatterjee et al. that the discounted version of the metric is characterized by the discounted quantitative game μ-calculus. In the discounted case, we show that the metric can be computed exactly by extending the method for Labelled Markov Chains by Chen et al. And in the undiscounted case, we prove that the problem whether the metric between two states is under a given threshold can be decided in NP∩coNP, which improves the previous PSPACE upperbound by Chatterjee et al.