Theory of linear and integer programming
Theory of linear and integer programming
A new approach to the maximum-flow problem
Journal of the ACM (JACM)
A fast parametric maximum flow algorithm and applications
SIAM Journal on Computing
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Model checking and abstraction
ACM Transactions on Programming Languages and Systems (TOPLAS)
Deciding bisimilarity and similarity for probabilistic processes
Journal of Computer and System Sciences
Communication and Concurrency
Recent Developments in Maximum Flow Algorithms (Invited Lecture)
SWAT '98 Proceedings of the 6th Scandinavian Workshop on Algorithm Theory
Can A Maximum Flow be Computed on o(nm) Time?
ICALP '90 Proceedings of the 17th International Colloquium on Automata, Languages and Programming
Simulation for Continuous-Time Markov Chains
CONCUR '02 Proceedings of the 13th International Conference on Concurrency Theory
Simulations Between Specifications of Distributed Systems
CONCUR '91 Proceedings of the 2nd International Conference on Concurrency Theory
Verifying Continuous Time Markov Chains
CAV '96 Proceedings of the 8th International Conference on Computer Aided Verification
Computing simulations on finite and infinite graphs
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Model-Checking Algorithms for Continuous-Time Markov Chains
IEEE Transactions on Software Engineering
From Bisimulation to Simulation: Coarsest Partition Problems
Journal of Automated Reasoning
Probabilistic weak simulation is decidable in polynomial time
Information Processing Letters
Comparative branching-time semantics for Markov chains
Information and Computation
An Experimental Evaluation of Probabilistic Simulation
FORTE '08 Proceedings of the 28th IFIP WG 6.1 international conference on Formal Techniques for Networked and Distributed Systems
A Space-Efficient Probabilistic Simulation Algorithm
CONCUR '08 Proceedings of the 19th international conference on Concurrency Theory
Abstraction for Stochastic Systems by Erlang's Method of Stages
CONCUR '08 Proceedings of the 19th international conference on Concurrency Theory
Three-valued abstraction for continuous-time Markov chains
CAV'07 Proceedings of the 19th international conference on Computer aided verification
Deciding simulations on probabilistic automata
ATVA'07 Proceedings of the 5th international conference on Automated technology for verification and analysis
A counterexample-guided abstraction-refinement framework for markov decision processes
ACM Transactions on Computational Logic (TOCL)
Bisimulation Metrics for Continuous Markov Decision Processes
SIAM Journal on Computing
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Abstraction techniques based on simulation relations have become an important and effective proof technique to avoid the infamous state space explosion problem. In the context of Markov chains, strong and weak simulation relations have been proposed [17,6], together with corresponding decision algorithms [3,5], but it is as yet unclear whether they can be used as effectively as their non-stochastic counterparts. This paper presents drastically improved algorithms to decide whether one (discrete- or continuous-time) Markov chain strongly or weakly simulates another. The key innovation is the use of parametric maximum flow techniques to amortize computations.