Regional Multi-Armed Bandits

  title={Regional Multi-Armed Bandits},
  author={Zhiyang Wang and Ruida Zhou and Cong Shen},
We consider a variant of the classic multiarmed bandit problem where the expected reward of each arm is a function of an unknown parameter. The arms are divided into different groups, each of which has a common parameter. Therefore, when the player selects an arm at each time slot, information of other arms in the same group is also revealed. This regional bandit model naturally bridges the non-informative bandit setting where the player can only learn the chosen arm, and the global bandit… CONTINUE READING
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