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Sterre Lutz

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Preprint Aug 2026

Optimizing Minimax Regret in Uncertain MDPs with Small Sets of Policies

Sequential decision-making in real-world applications often involves uncertainty about the environment's model. Uncertain Markov decision processes (UMDPs) represent the possible environments as a set of MDPs with shared states and actions but potentially different transition probabilities and rewards. Optimizing a sin...

Sterre Lutz, D. Vos, M. Spaan et al. · 0 citations

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