3 citations · 9 across the 10 of their papers we have counts for
6 papers · 1 filter
Optimal Cost Almost-sure Reachability in POMDPs
Krishnendu Chatterjee, Martin Chmelík, Raghav Gupta +1
We consider partially observable Markov decision processes (POMDPs) with a set of target states and every transition is associated with an integer cost. The optimization objective…
Temporal Logic Control for Stochastic Linear Systems using Abstraction Refinement of Probabilistic Games
Maria Svorenova, Jan Kretinsky, Martin Chmelik +3
We consider the problem of computing the set of initial states of a dynamical system such that there exists a control strategy to ensure that the trajectories satisfy a temporal lo…
Qualitative Analysis of POMDPs with Temporal Logic Specifications for Robotics Applications
Krishnendu Chatterjee, Martin Chmelík, Raghav Gupta +1
We consider partially observable Markov decision processes (POMDPs), that are a standard framework for robotics applications to model uncertainties present in the real world, with…
POMDPs under Probabilistic Semantics
Krishnendu Chatterjee, Martin Chmelik
We consider partially observable Markov decision processes (POMDPs) with limit-average payoff, where a reward value in the interval [0,1] is associated to every transition, and the…
CEGAR for Qualitative Analysis of Probabilistic Systems
Krishnendu Chatterjee, Martin Chmelik, Przemyslaw Daca
We consider Markov decision processes (MDPs) which are a standard model for probabilistic systems. We focus on qualitative properties for MDPs that can express that desired behavio…
Verification of Markov Decision Processes using Learning Algorithms
Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelík +5
We present a general framework for applying machine-learning algorithms to the verification of Markov decision processes (MDPs). The primary goal of these techniques is to improve…