Related papers: Communication-Efficient Collaborative Best Arm Identification

Communication-Efficient Collaborative Best Arm Identification

URL: http://arxiv.org/abs/2208.09029v1
Date: Thu, 18 Aug 2022 19:02:29 GMT
Title: Communication-Efficient Collaborative Best Arm Identification
Authors: Nikolai Karpov and Qin Zhang
Abstract summary: We investigate top-$m$ arm identification, a basic problem in bandit theory, in a multi-agent learning model in which agents collaborate to learn an objective function. We are interested in designing collaborative learning algorithms that achieve maximum speedup.
Score: 6.861971769602314
License: http://creativecommons.org/licenses/by/4.0/
Abstract: We investigate top-$m$ arm identification, a basic problem in bandit theory, in a multi-agent learning model in which agents collaborate to learn an objective function. We are interested in designing collaborative learning algorithms that achieve maximum speedup (compared to single-agent learning algorithms) using minimum communication cost, as communication is frequently the bottleneck in multi-agent learning. We give both algorithmic and impossibility results, and conduct a set of experiments to demonstrate the effectiveness of our algorithms.

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