A General Auxiliary Controller for Multi-agent Flocking

TL;DR

This paper introduces a general auxiliary controller that uses a confidence score to enhance multi-agent flocking by prioritizing influential agents, improving coordination across various algorithms and settings.

Contribution

The paper proposes a novel confidence score and auxiliary controller that improve multi-agent flocking performance across different algorithms and conditions.

Findings

Enhanced flocking performance with the auxiliary controller.

Effective across learning-based and non-learning-based algorithms.

Improved robustness under varying communication and initial conditions.

Abstract

We aim to improve the performance of multi-agent flocking behavior by quantifying the structural significance of each agent. We designed a confidence score(ConfScore) to measure the spatial significance of each agent. The score will be used by an auxiliary controller to refine the velocity of agents. The agents will be enforced to follow the motion of the leader agents whose ConfScores are high. We demonstrate the efficacy of the auxiliary controller by applying it to several existing algorithms including learning-based and non-learning-based methods. Furthermore, we examined how the auxiliary controller can help improve the performance under different settings of communication radius, number of agents and maximum initial velocity.