Complexity of deciding Tarski algebra
Journal of Symbolic Computation
Bisimulation through probabilistic testing
Information and Computation
The complexity of probabilistic verification
Journal of the ACM (JACM)
The complexity of mean payoff games on graphs
Theoretical Computer Science
Probabilistic simulations for probabilistic processes
Nordic Journal of Computing
Infinite Games and Verification (Extended Abstract of a Tutorial)
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
How to Specify and Verify the Long-Run Average Behavior of Probabilistic Systems
LICS '98 Proceedings of the 13th Annual IEEE Symposium on Logic in Computer Science
Stochastic Games with Branching-Time Winning Objectives
LICS '06 Proceedings of the 21st Annual IEEE Symposium on Logic in Computer Science
QEST '07 Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems
FSTTCS '05 Proceedings of the 25th international conference on Foundations of Software Technology and Theoretical Computer Science
On the controller synthesis for finite-state markov decision processes
FSTTCS '05 Proceedings of the 25th international conference on Foundations of Software Technology and Theoretical Computer Science
Synthesis of optimal switching logic for hybrid systems
EMSOFT '11 Proceedings of the ninth ACM international conference on Embedded software
On Almost-Sure Properties of Probabilistic Discrete Event Systems
Fundamenta Informaticae - Theory that Counts: To Oscar Ibarra on His 70th Birthday
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We study the problem of effective controller synthesis for finite-state Markov decision processes (MDPs) and the class of properties definable in the logic PCTL extended with long-run average propositions. We show that the existence of such a controller is decidable, and we give an algorithm which computes the controller if it exists. We also address the issue of "controller robustness", i.e., the problem whether there is a controller which still guarantees the satisfaction of a given property when the probabilities in the considered MDP slightly deviate from their original values. From a practical point of view, this is an important aspect since the probabilities are often determined empirically and hence they are inherently imprecise. We show that the existence of robust controllers is also decidable, and that such controllers are effectively computable if they exist.