# Distributed Bandits: Probabilistic Communication on d-regular Graphs

arXiv: https://arxiv.org/abs/2011.07720 · HTML: https://mlsanity.com/paper/2011.07720/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Nov 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)
- [Flooding with Absorption: An Efficient Protocol for Heterogeneous Bandits over Complex Networks](https://mlsanity.com/paper/2303.05445/) (2023)

## Abstract (arXiv)

We study the decentralized multi-agent multi-armed bandit problem for agents that communicate with probability over a network defined by a d-regular graph. Every edge in the graph has probabilistic weight p to account for the (1!-!p) probability of a communication link failure. At each time step, each agent chooses an arm and receives a numerical reward associated with the chosen arm. After each choice, each agent observes the last obtained reward of each of its neighbors with probability p. We propose a new Upper Confidence Bound (UCB) based algorithm and analyze how agent-based strategies contribute to minimizing group regret in this probabilistic communication setting. We provide theoretical guarantees that our algorithm outperforms state-of-the-art algorithms. We illustrate our results and validate the theoretical claims using numerical simulations.