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A Novel Confidence-Based Algorithm for Structured Bandits
[article]
2020
arXiv
pre-print
We study finite-armed stochastic bandits where the rewards of each arm might be correlated to those of other arms. We introduce a novel phased algorithm that exploits the given structure to build confidence sets over the parameters of the true bandit problem and rapidly discard all sub-optimal arms. In particular, unlike standard bandit algorithms with no structure, we show that the number of times a suboptimal arm is selected may actually be reduced thanks to the information collected by
arXiv:2005.11593v1
fatcat:3dqqmxsg2bfy5isgx3ifikkhxe