Satisfiability bounds for ω-regular properties in bounded-parameter Markov decision processes
M Weininger, T Meggendorfer… - 2019 IEEE 58th …, 2019 - ieeexplore.ieee.org
We consider the problem of computing minimum and maximum probabilities of satisfying an
ω-regular property in a bounded-parameter Markov decision process (BMDP). BMDP arise …
ω-regular property in a bounded-parameter Markov decision process (BMDP). BMDP arise …
Polynomial-time alternating probabilistic bisimulation for interval MDPs
Abstract Interval Markov decision processes (IMDPs) extend classical MDPs by allowing
intervals to be used as transition probabilities. They provide a powerful modelling tool for …
intervals to be used as transition probabilities. They provide a powerful modelling tool for …
Decision algorithms for modelling, optimal control and verification of probabilistic systems
V Hashemi - 2017 - publikationen.sulb.uni-saarland.de
Markov Decision Processes (MDPs) constitute a mathematical framework for modelling
systems featuring both probabilistic and nondeterministic behaviour. They are widely used …
systems featuring both probabilistic and nondeterministic behaviour. They are widely used …
[PDF][PDF] Polynomial-Time Alternating Probabilistic Bisimulation for
Interval Markov decision processes (IMDPs) extend classical MDPs by allowing intervals to
be used as transition probabilities. They provide a powerful modelling tool for probabilistic …
be used as transition probabilities. They provide a powerful modelling tool for probabilistic …