2 citations · 5 across the 14 of their papers we have counts for
5 papers · 1 filter
Fast Computation of Conditional Probabilities in MDPs and Markov Chain Families
Milan Češka, Sebastian Junges, Luko van der Maas +2
Computing optimal conditional reachability probabilities in Markov decision processes (MDPs) is tractable by a reduction to reachability probabilities. Yet, this reduction yields c…
Shields to Guarantee Probabilistic Safety in MDPs
Linus Heck, Filip Macák, Roman Andriushchenko +2
Shielding is a prominent model-based technique to ensure safety of autonomous agents. Classical shielding aims to ensure that nothing bad ever happens and comes with strong guarant…
Generalized Parameter Lifting: Finer Abstractions for Parametric Markov Chains
Linus Heck, Tim Quatmann, Jip Spel +2
Parametric Markov chains (pMCs) are Markov chains (MCs) with symbolic probabilities. A pMC encodes a family of MCs, where each member is obtained by replacing parameters with const…
Tools at the Frontiers of Quantitative Verification
Roman Andriushchenko, Alexander Bork, Carlos E. Budde +20
The analysis of formal models that include quantitative aspects such as timing or probabilistic choices is performed by quantitative verification tools. Broad and mature tool suppo…
CTMCs with Imprecisely Timed Observations
Thom Badings, Matthias Volk, Sebastian Junges +2
Labeled continuous-time Markov chains (CTMCs) describe processes subject to random timing and partial observability. In applications such as runtime monitoring, we must incorporate…