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Towards Fundamental Limits of Multi-armed Bandits with Random Walk Feedback by Wang, Tianyu; Yang, Lin F.; Wang, Zizhuo is a scholarly article available to read on EtoBox.

What is Towards Fundamental Limits of Multi-armed Bandits with Random Walk Feedback about?

In this paper, we consider a new Multi-Armed Bandit (MAB) problem where arms are nodes in an unknown and possibly changing graph, and the agent (i) initiates random walks over the graph by pulling arms, (ii) observes the random walk trajectories, and (iii) receives rewards equal to the lengths of the walks. We provide a comprehensive understanding of this problem by studying both the stochastic and the adversarial setting. We show that this problem is not easier than a standard MAB in an information theoretical sense, although additional information is available through random walk trajectories. Behaviors of bandit algorithms on this problem are also studied.

Author

Wang, Tianyu; Yang, Lin F.; Wang, Zizhuo

Published

2020

Language

EN