Generalizing distribution of partial rewards for multi-armed bandits with temporally-partitioned rewards. (arXiv:2211.06883v1 [cs.LG])

We investigate the Multi-Armed Bandit problem with Temporally-Partitioned
Rewards (TP-MAB) setting in this paper. In the TP-MAB setting, an agent will
receive subsets of the reward over multiple rounds rather than the entire
reward for the arm all at once. In this paper, we introduce a general
formulation of how an arm's cumulative reward is distributed across several
rounds, called Beta-spread property. Such a generalization is needed to be able
to handle partitioned rewards in which the maximum reward per …

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