Reactive, generative, and stratified models of probabilistic processes
Information and Computation
Composition and behaviors of probabilistic I/O automata
Theoretical Computer Science
Model Checking of Probabalistic and Nondeterministic Systems
Proceedings of the 15th Conference on Foundations of Software Technology and Theoretical Computer Science
Compositional Analysis of Expected Delays in Networks of Probabilistic I/O Automata
LICS '98 Proceedings of the 13th Annual IEEE Symposium on Logic in Computer Science
Journal of Automata, Languages and Combinatorics - Special issue: Selected papers of the workshop weighted automata: Theory and applications (Dresden University of Technology (Germany), March 4-8, 2002)
Quantitative model checking revisited: neither decidable nor approximable
FORMATS'07 Proceedings of the 5th international conference on Formal modeling and analysis of timed systems
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
Partial Order Reduction for Probabilistic Systems: A Revision for Distributed Schedulers
CONCUR 2009 Proceedings of the 20th International Conference on Concurrency Theory
On the Expressive Power of Schedulers in Distributed Probabilistic Systems
Electronic Notes in Theoretical Computer Science (ENTCS)
Verification of partial-information probabilistic systems using counterexample-guided refinements
ATVA'12 Proceedings of the 10th international conference on Automated Technology for Verification and Analysis
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We consider the Probabilistic I/O Automata framework, for which we address the verification of reachability properties in case the rates (also called delay parameters) are unspecified. We show that the problem of finding (or even approximating) the supremum probability that a set of states is reached is undecidable. However, we give an algorithm to obtain a non-trivial over-estimation of this value. We explain why this over-estimation may result useful for many systems. Finally, in order to compare our approach against Markov Decision Processes, we study a simple protocol for anonymous fair service. In this case, the over-estimation computed over the PIOA gives a more realistic result than the exact computation over the MDP.