4 papers · 1 filter
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…
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…
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…
Certifiably Robust Policies for Uncertain Parametric Environments
Yannik Schnitzer, Alessandro Abate, David Parker
We present a data-driven approach for producing policies that are provably robust across unknown stochastic environments. Existing approaches can learn models of a single environme…