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Hannes Eriksson

2 accepted papers

2023

Minimax-Bayes Reinforcement Learning

AISTATS 2023poster

While the Bayesian decision-theoretic framework offers an elegant solution to the problem of decision making under uncertainty, one question is how to appropriately select the prior distribution. One idea is to employ a worst-case prior. However, this is not as easy to specify in sequential decision…

2022

SENTINEL: taming uncertainty with ensemble based distributional reinforcement learning

UAI 2022poster

In this paper, we consider risk-sensitive sequential decision-making in Reinforcement Learning (RL). Our contributions are two-fold. First, we introduce a novel and coherent quantification of risk, namely composite risk, which quantifies the joint effect of aleatory and epistemic risk during the le…

Cited by 29SourcePDFScholar