activity
20232026
most citedCTMCs with Imprecisely Timed Observations

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CC2026

On the Computational Complexity of Hidden Markov Model Identification

Markel Zubia, Nils Jansen

Identification is the task of recovering the parameters of an unknown ground-truth model from sampled data. When parameters other than the ground truth induce the same output distr…

cs.GT2026

Resilient Strategies for Stochastic Systems: How Much Does It Take to Break a Winning Strategy?

Kush Grover, Markel Zubia, Debraj Chakraborty +3

We study the problem of resilient strategies in the presence of uncertainty. Resilient strategies enable an agent to make decisions that are robust against disturbances. In particu…

cs.AI2024

Robust Markov Decision Processes: A Place Where AI and Formal Methods Meet

Marnix Suilen, Thom Badings, Eline M. Bovy +2

Markov decision processes (MDPs) are a standard model for sequential decision-making problems and are widely used across many scientific areas, including formal methods and artific…

cs.LG2024

Policy Verification in Stochastic Dynamical Systems Using Logarithmic Neural Certificates

Thom Badings, Wietze Koops, Sebastian Junges +1

We consider the verification of neural network policies for discrete-time stochastic systems with respect to reach-avoid specifications. We use a learner-verifier procedure that le…

eess.SY2024

A Stability-Based Abstraction Framework for Reach-Avoid Control of Stochastic Dynamical Systems with Unknown Noise Distributions

Thom Badings, Licio Romao, Alessandro Abate +1

Finite-state abstractions are widely studied for the automated synthesis of correct-by-construction controllers for stochastic dynamical systems. However, existing abstraction meth…

cs.LO2024★ 1 cited

CTMCs with Imprecisely Timed Observations

Thom Badings, Matthias Volk, Sebastian Junges +2

Labeled continuous-time Markov chains (CTMCs) describe processes subject to random timing and partial observability. In applications such as runtime monitoring, we must incorporate…

eess.SY2023

Correct-by-Construction Control for Stochastic and Uncertain Dynamical Models via Formal Abstractions

Thom Badings, Nils Jansen, Licio Romao +1

Automated synthesis of correct-by-construction controllers for autonomous systems is crucial for their deployment in safety-critical scenarios. Such autonomous systems are naturall…