2026
Dynamic Programming for Epistemic Uncertainty in Markov Decision Processes
ICML 2026spotlight
In this paper, we propose a general theory of ambiguity-averse MDPs, which treats the uncertain transition probabilities as random variables and evaluates a policy via a risk measure applied to its random return. This ambiguity-averse MDP framework unifies several models of MDPs with epistemic uncer…