Multi-User MABs with User Dependent Rewards for Uncoordinated Spectrum Access
Information Theory
2019-12-05 v3 Machine Learning
Networking and Internet Architecture
math.IT
Machine Learning
Abstract
Multi-user multi-armed bandits have emerged as a good model for uncoordinated spectrum access problems. In this paper we consider the scenario where users cannot communicate with each other. In addition, the environment may appear differently to different users, , the mean rewards as observed by different users for the same channel may be different. With this setup, we present a policy that achieves a regret of . This paper has been accepted at Asilomar Conference on Signals, Systems, and Computers 2019.
Cite
@article{arxiv.1910.09091,
title = {Multi-User MABs with User Dependent Rewards for Uncoordinated Spectrum Access},
author = {Akshayaa Magesh and Venugopal V. Veeravalli},
journal= {arXiv preprint arXiv:1910.09091},
year = {2019}
}