Decentralized Multi-player Multi-armed Bandits with No Collision Information

02/29/2020
by   Chengshuai Shi, et al.
0

The decentralized stochastic multi-player multi-armed bandit (MP-MAB) problem, where the collision information is not available to the players, is studied in this paper. Building on the seminal work of Boursier and Perchet (2019), we propose error correction synchronization involving communication (EC-SIC), whose regret is shown to approach that of the centralized stochastic MP-MAB with collision information. By recognizing that the communication phase without collision information corresponds to the Z-channel model in information theory, the proposed EC-SIC algorithm applies optimal error correction coding for the communication of reward statistics. A fixed message length, as opposed to the logarithmically growing one in Boursier and Perchet (2019), also plays a crucial role in controlling the communication loss. Experiments with practical Z-channel codes, such as repetition code, flip code and modified Hamming code, demonstrate the superiority of EC-SIC in both synthetic and real-world datasets.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/25/2021

Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions

We study a new stochastic multi-player multi-armed bandits (MP-MAB) prob...
research
04/28/2019

Non-Stochastic Multi-Player Multi-Armed Bandits: Optimal Rate With Collision Information, Sublinear Without

We consider the non-stochastic version of the (cooperative) multi-player...
research
11/02/2020

On No-Sensing Adversarial Multi-player Multi-armed Bandits with Collision Communications

We study the notoriously difficult no-sensing adversarial multi-player m...
research
09/21/2018

SIC-MMAB: Synchronisation Involves Communication in Multiplayer Multi-Armed Bandits

We consider the stochastic multiplayer multi-armed bandit problem, where...
research
04/28/2022

Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms: Learning Algorithms Applications

Multi-player multi-armed bandits (MMAB) study how decentralized players ...
research
02/19/2021

A High Performance, Low Complexity Algorithm for Multi-Player Bandits Without Collision Sensing Information

Motivated by applications in cognitive radio networks, we consider the d...
research
07/20/2023

Decentralized Smart Charging of Large-Scale EVs using Adaptive Multi-Agent Multi-Armed Bandits

The drastic growth of electric vehicles and photovoltaics can introduce ...

Please sign up or login with your details

Forgot password? Click here to reset