First claimed regret bound for non-stationary restless multi-armed bandits via per-arm sliding-window optimism, but it holds for a relaxed regret measure and the proof contains gaps.
Reinforcement learning for non- stationary markov decision processes: The blessing of (more) optimism
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
REJECT 1roles
background 1polarities
background 1representative citing papers
citing papers explorer
-
Non-Stationary Restless Multi-Armed Bandits with Provable Guarantee
First claimed regret bound for non-stationary restless multi-armed bandits via per-arm sliding-window optimism, but it holds for a relaxed regret measure and the proof contains gaps.