no code implementations • 14 Mar 2024 • Tomáš Brázdil, Krishnendu Chatterjee, Martin Chmelik, Vojtěch Forejt, Jan Křetínský, Marta Kwiatkowska, Tobias Meggendorfer, David Parker, Mateusz Ujma
The presented framework focuses on probabilistic reachability, which is a core problem in verification, and is instantiated in two distinct scenarios.
no code implementations • 29 Sep 2017 • Krishnendu Chatterjee, Martin Chmelik, Ufuk Topcu
Partially observable Markov decision processes (POMDPs) are widely used in probabilistic planning problems in which an agent interacts with an environment using noisy and imprecise sensors.
no code implementations • 26 Nov 2015 • Krishnendu Chatterjee, Martin Chmelik, Jessica Davies
POMDPs are standard models for probabilistic planning problems, where an agent interacts with an uncertain environment.
no code implementations • 9 Aug 2014 • Krishnendu Chatterjee, Martin Chmelik
We consider two types of path constraints: (i) quantitative constraint defines the set of paths where the payoff is at least a given threshold lambda_1 in (0, 1]; and (ii) qualitative constraint which is a special case of quantitative constraint with lambda_1=1.
