51 citations · 233 across the 33 of their papers we have counts for
7 papers · 1 filter
Online Monitoring -Regular Properties in Unknown Markov Chains
Javier Esparza, Stefan Kiefer, Jan Kretinsky +1
We study runtime monitoring of -regular properties. We consider a simple setting in which a run of an unknown finite-state Markov chain is monitored against a fixed…
Comparison of Algorithms for Simple Stochastic Games
Jan Křetínský, Emanuel Ramneantu, Alexander Slivinskiy +1
Simple stochastic games are turn-based 2.5-player zero-sum graph games with a reachability objective. The problem is to compute the winning probability as well as the optimal strat…
Comparison of Algorithms for Simple Stochastic Games (Full Version)
Jan Kretinsky, Emanuel Ramneantu, Alexander Slivinskiy +1
Simple stochastic games are turn-based 2.5-player zero-sum graph games with a reachability objective. The problem is to compute the winning probability as well as the optimal strat…
Anytime Guarantees for Reachability in Uncountable Markov Decision Processes
Kush Grover, Jan Křetínský, Tobias Meggendorfer +1
We consider the problem of approximating the reachability probabilities in Markov decision processes (MDP) with uncountable (continuous) state and action spaces. While there are al…
Automata Tutor v3
Loris D'Antoni, Martin Helfrich, Jan Kretinsky +2
Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer…
Stochastic Games with Lexicographic Reachability-Safety Objectives
Krishnendu Chatterjee, Joost-Pieter Katoen, Maximilian Weininger +1
We study turn-based stochastic zero-sum games with lexicographic preferences over reachability and safety objectives. Stochastic games are standard models in control, verification,…
dtControl: Decision Tree Learning Algorithms for Controller Representation
Pranav Ashok, Mathias Jackermeier, Pushpak Jagtap +3
Decision tree learning is a popular classification technique most commonly used in machine learning applications. Recent work has shown that decision trees can be used to represent…