# Distributed Learning: Sequential Decision Making in Resource-Constrained Environments

arXiv: https://arxiv.org/abs/2004.06171 · HTML: https://mlsanity.com/paper/2004.06171/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2020.

## Built on by (most cited first, 2 of 2)

- [One More Step Towards Reality: Cooperative Bandits with Imperfect Communication](https://mlsanity.com/paper/2111.12482/) (2021)
- [When to Call Your Neighbor? Strategic Communication in Cooperative Stochastic Bandits](https://mlsanity.com/paper/2110.04396/) (2021)

## Abstract (arXiv)

We study cost-effective communication strategies that can be used to improve the performance of distributed learning systems in resource-constrained environments. For distributed learning in sequential decision making, we propose a new cost-effective partial communication protocol. We illustrate that with this protocol the group obtains the same order of performance that it obtains with full communication. Moreover, we prove that under the proposed partial communication protocol the communication cost is O(log T), where T is the time horizon of the decision-making process. This improves significantly on protocols with full communication, which incur a communication cost that is O(T). We validate our theoretical results using numerical simulations.