Sparse Control of Multiagent Systems

TL;DR

This paper reviews the limitations of decentralized social dynamics control and explores the possibility of using sparse external interventions to steer multiagent systems toward desired configurations.

Contribution

It introduces the concept of sparse control strategies for finite multiagent models to efficiently achieve specific social patterns.

Findings

Identifies limitations of decentralized controls in social dynamics.

Proposes sparse control methods for guiding multiagent systems.

Analyzes conditions for effective external influence.

Abstract

In recent years, numerous studies have focused on the mathematical modeling of social dynamics, with self-organization, i.e., the autonomous pattern formation, as the main driving concept. Usually, first or second order models are employed to reproduce, at least qualitatively, certain global patterns (such as bird flocking, milling schools of fish or queue formations in pedestrian flows, just to mention a few). It is, however, common experience that self-organization does not always spontaneously occur in a society. In this review chapter we aim to describe the limitations of decentralized controls in restoring certain desired configurations and to address the question of whether it is possible to externally and parsimoniously influence the dynamics to reach a given outcome. More specifically, we address the issue of finding the sparsest control strategy for finite agent-based models in order to lead the dynamics optimally towards a desired pattern.