Design of heterogeneous multi-agent system for distributed computation

TL;DR

This paper proposes a method for designing heterogeneous multi-agent systems where the collective behavior follows an averaged dynamics, enabling robust, initialization-free distributed algorithms for various tasks.

Contribution

It introduces a design framework for heterogeneous multi-agent systems based on averaged dynamics, including nonlinear couplings, for distributed computation tasks.

Findings

Effective estimation of network size

Distributed optimization algorithms

Robust synchronization of oscillators

Abstract

A group behavior of a heterogeneous multi-agent system is studied which obeys an "average of individual vector fields" under strong couplings among the agents. Under stability of the averaged dynamics (not asking stability of individual agents), the behavior of heterogeneous multi-agent system can be estimated by the solution to the averaged dynamics. A following idea is to "design" individual agent's dynamics such that the averaged dynamics performs the desired task. A few applications are discussed including estimation of the number of agents in a network, distributed least-squares or median solver, distributed optimization, distributed state estimation, and robust synchronization of coupled oscillators. Since stability of the averaged dynamics makes the initial conditions forgotten as time goes on, these algorithms are initialization-free and suitable for plug-and-play operation. At last, nonlinear couplings are also considered, which potentially asserts that enforced synchronization gives rise to an emergent behavior of a heterogeneous multi-agent system.