Yannik Schnitzer — accepted AI-conference papers

2026

Efficient Solution and Learning of Robust Factored MDPs

Yannik Schnitzer, Alessandro Abate, David Parker

AAAI 2026technical

Robust Markov decision processes (r-MDPs) extend MDPs by explicitly modelling epistemic uncertainty about transition dynamics. Learning r-MDPs from interactions with an unknown environment enables the synthesis of robust policies with provable (PAC) guarantees on performance, but this can require a

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2026

Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning

Yannik Schnitzer, Mathias Jackermeier, Alessandro Abate, David Parker

ICML 2026poster

Multi-task reinforcement learning trains generalist policies that can execute multiple tasks. While recent years have seen significant progress, existing approaches rarely provide formal performance guarantees, which are indispensable when deploying policies in safety-critical settings. We present a…

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