9 papers
Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning
Yannik Schnitzer, Mathias Jackermeier, Alessandro Abate +1
Multi-task reinforcement learning trains generalist policies that can execute multiple tasks. While recent years have seen significant progress, existing approaches rarely provide…
Robust Parameter Learning for Uncertain MDPs
Yannik Schnitzer, Alessandro Abate, David Parker
Learning-based approaches to verifying unknown Markov decision processes (MDPs) often employ uncertain MDPs. These models use, for example, confidence intervals to capture transiti…
Multi-Property Synthesis
Christoph Weinhuber, Yannik Schnitzer, Alessandro Abate +3
We study LTLf synthesis with multiple properties, where satisfying all properties may be impossible. Instead of enumerating subsets of properties, we compute in one fixed-point com…
Efficient Solution and Learning of Robust Factored MDPs
Yannik Schnitzer, Alessandro Abate, David Parker
Robust Markov decision processes (r-MDPs) extend MDPs by explicitly modelling epistemic uncertainty about transition dynamics. Learning r-MDPs from interactions with an unknown env…
Existence and Synthesis of Multi-Resolution Approximate Bisimulations for Continuous-State Dynamical Systems
Rudi Coppola, Yannik Schnitzer, Mirco Giacobbe +2
We present a fully automatic framework for synthesising compact, finite-state deterministic abstractions of deterministic, continuous-state autonomous systems under locally specifi…
Branching Bisimulation Learning
Alessandro Abate, Mirco Giacobbe, Christian Micheletti +1
We introduce a bisimulation learning algorithm for non-deterministic transition systems. We generalise bisimulation learning to systems with bounded branching and extend its applic…