activity
20172022
most citedFaster Algorithms for Mean-Payoff Parity Games

1 citations · 1 across the 2 of their papers we have counts for

collaborators

7 papers

cs.LO2022

Leveraging the Power of Graph Algorithms: Efficient Algorithms for Computer-Aided Verification

Alexander Svozil

The goal of the thesis is to leverage fast graph algorithms and modern algorithmic techniques for problems in model checking and synthesis on graphs, MDPs, and game graphs. The res…

cs.LO2021

Symbolic Time and Space Tradeoffs for Probabilistic Verification

Krishnendu Chatterjee, Wolfgang Dvořák, Monika Henzinger +1

We present a faster symbolic algorithm for the following central problem in probabilistic verification: Compute the maximal end-component (MEC) decomposition of Markov decision pro…

cs.GT2019

Near-Linear Time Algorithms for Streett Objectives in Graphs and MDPs

Krishnendu Chatterjee, Wolfgang Dvorák, Monika Henzinger +1

The fundamental model-checking problem, given as input a model and a specification, asks for the algorithmic verification of whether the model satisfies the specification. Two clas…

cs.GT2019

Quasipolynomial Set-Based Symbolic Algorithms for Parity Games

Krishnendu Chatterjee, Wolfgang Dvořák, Monika Henzinger +1

Solving parity games, which are equivalent to modal -calculus model checking, is a central algorithmic problem in formal methods. Besides the standard computation model with the…

cs.DS2019

Fully Dynamic k-Center Clustering in Doubling Metrics

Gramoz Goranci, Monika Henzinger, Dariusz Leniowski +2

Clustering is one of the most fundamental problems in unsupervised learning with a large number of applications. However, classical clustering algorithms assume that the data is st…

cs.DS2018

Algorithms and Conditional Lower Bounds for Planning Problems

Krishnendu Chatterjee, Wolfgang Dvořák, Monika Henzinger +1

We consider planning problems for graphs, Markov decision processes (MDPs), and games on graphs. While graphs represent the most basic planning model, MDPs represent interaction wi…