activity
20182021
most citedComparison of Algorithms for Simple Stochastic Games

8 citations · 10 across the 2 of their papers we have counts for

collaborators

8 papers

cs.GT20212 cited

Stochastic Games with Disjunctions of Multiple Objectives

Tobias Winkler, Maximilian Weininger

Stochastic games combine controllable and adversarial non-determinism with stochastic behavior and are a common tool in control, verification and synthesis of reactive systems faci…

cs.AI2021

dtControl 2.0: Explainable Strategy Representation via Decision Tree Learning Steered by Experts

Pranav Ashok, Mathias Jackermeier, Jan Křetínský +3

Recent advances have shown how decision trees are apt data structures for concisely representing strategies (or controllers) satisfying various objectives. Moreover, they also make…

cs.GT20208 cited

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…

cs.FL2020

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…

cs.LG2020

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…

cs.GT2019

Approximating Values of Generalized-Reachability Stochastic Games

Pranav Ashok, Krishnendu Chatterjee, Jan Kretinsky +2

Simple stochastic games are turn-based 2.5-player games with a reachability objective. The basic question asks whether one player can ensure reaching a given target with at least a…