Interval abstraction plus big time steps semantics yields the first general effective model checker for stochastic automata with arbitrary distributions.
31 Arnd Hartmanns and Benjamin Lucien Kaminski
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Tractable relational probabilistic hyperproperties for MDPs are identified with efficient algorithms for probability-equality queries on reachability and omega-regular events, plus hardness results and a fast implementation.
Introduces and implements confidence sequences for online statistical model checking of MDPs that require 50x fewer samples than prior state-of-the-art union-bound approaches.
citing papers explorer
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Effective Stochastic Automata Model Checking by Interval Abstraction (extended version)
Interval abstraction plus big time steps semantics yields the first general effective model checker for stochastic automata with arbitrary distributions.
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Tractable Hyperproperties for MDPs
Tractable relational probabilistic hyperproperties for MDPs are identified with efficient algorithms for probability-equality queries on reachability and omega-regular events, plus hardness results and a fast implementation.