59 citations · 191 across the 36 of their papers we have counts for
9 papers · 1 filter
Abstraction-Refinement for Hierarchical Probabilistic Models
Sebastian Junges, Matthijs T. J. Spaan
Markov decision processes are a ubiquitous formalism for modelling systems with non-deterministic and probabilistic behavior. Verification of these models is subject to the famous…
Safe Reinforcement Learning via Shielding under Partial Observability
Steven Carr, Nils Jansen, Sebastian Junges +1
Safe exploration is a common problem in reinforcement learning (RL) that aims to prevent agents from making disastrous decisions while exploring their environment. A family of appr…
Robust Finite-State Controllers for Uncertain POMDPs
Murat Cubuktepe, Nils Jansen, Sebastian Junges +3
Uncertain partially observable Markov decision processes (uPOMDPs) allow the probabilistic transition and observation functions of standard POMDPs to belong to a so-called uncertai…
Enforcing Almost-Sure Reachability in POMDPs
Sebastian Junges, Nils Jansen, Sanjit A. Seshia
Partially-Observable Markov Decision Processes (POMDPs) are a well-known stochastic model for sequential decision making under limited information. We consider the EXPTIME-hard pro…
Verification of indefinite-horizon POMDPs
Alexander Bork, Sebastian Junges, Joost-Pieter Katoen +1
The verification problem in MDPs asks whether, for any policy resolving the nondeterminism, the probability that something bad happens is bounded by some given threshold. This veri…
The Partially Observable Games We Play for Cyber Deception
Mohamadreza Ahmadi, Murat Cubuktepe, Nils Jansen +3
Progressively intricate cyber infiltration mechanisms have made conventional means of defense, such as firewalls and malware detectors, incompetent. These sophisticated infiltratio…
Safe Reinforcement Learning via Probabilistic Shields
Nils Jansen, Bettina Könighofer, Sebastian Junges +2
This paper targets the efficient construction of a safety shield for decision making in scenarios that incorporate uncertainty. Markov decision processes (MDPs) are prominent model…
Synthesis in pMDPs: A Tale of 1001 Parameters
Murat Cubuktepe, Nils Jansen, Sebastian Junges +2
This paper considers parametric Markov decision processes (pMDPs) whose transitions are equipped with affine functions over a finite set of parameters. The synthesis problem is to…
Probabilistic Model Checking for Complex Cognitive Tasks -- A case study in human-robot interaction
Sebastian Junges, Nils Jansen, Joost-Pieter Katoen +1
This paper proposes to use probabilistic model checking to synthesize optimal robot policies in multi-tasking autonomous systems that are subject to human-robot interaction. Given…