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Worst-Case Bayesian CVaR Regret Bounds for Episodic Markov Decision Processes
arXiv math.IT0 views
arXiv:2610.28157v1 Announce Type: new Abstract: We study the worst-case, over priors, Bayesian conditional value-at-risk (CVaR) of cumulative pseudo-regret in time-homogeneous finite-horizon episodic Markov decision processes. A high-probability guarantee for UCBVI-BF yields a prior-predictive upper bound. A lower bound follows by a three-state MDP and applying a reverse-KL inequality. For a constant number of states, the bounds have the same polynomial dependence on horizon, actions, and episodes, with a logarithmic gap in the risk level.
Source:https://arxiv.org/abs/2610.28157PreviousLower bounds for Bayesian CVaR in interactive problems with local differential privacyNextExact Storage-Repair-Bandwidth Tradeoffs for $(6,5,5)$ and $(7,6,6)$ Exact-Repair Regenerating Codes
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