SEA-PARAM: Exploring Schedulers in Parametric MDPs

Sebastian Arming
(University of Salzburg)
Ezio Bartocci
(TU Wien)
Ana Sokolova

We study parametric Markov decision processes (PMDPs) and their reachability probabilities "independent" of the parameters. Different to existing work on parameter synthesis (implemented in the tools PARAM and PRISM), our main focus is on describing different types of optimal deterministic memoryless schedulers for the whole parameter range. We implement a simple prototype tool SEA-PARAM that computes these optimal schedulers and show experimental results.

In Herbert Wiklicky and Erik de Vink: Proceedings 15th Workshop on Quantitative Aspects of Programming Languages and Systems (QAPL 2017), Uppsala, Sweden, 23rd April 2017, Electronic Proceedings in Theoretical Computer Science 250, pp. 25–38.
Published: 12th July 2017.

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