Controlling Self-Organizing Dynamics on Networks Using Models that Self-Organize

TL;DR

This paper develops a model for controlling self-organizing systems like sandpile networks, enabling the study of control strategies that influence cascade frequency and systemic risk, with potential applications to various self-organizing systems.

Contribution

It introduces a model capturing self-organizing mechanisms of SOC systems on networks and demonstrates optimal control strategies for managing cascade dynamics.

Findings

Optimal control strategies exist for generic cost functions.

Controlling a subcritical system can induce criticality.

The approach can be applied to other self-organizing systems.

Abstract

Controlling self-organizing systems is challenging because the system responds to the controller. Here we develop a model that captures the essential self-organizing mechanisms of Bak-Tang-Wiesenfeld (BTW) sandpiles on networks, a self-organized critical (SOC) system. This model enables studying a simple control scheme that determines the frequency of cascades and that shapes systemic risk. We show that optimal strategies exist for generic cost functions and that controlling a subcritical system may drive it to criticality. This approach could enable controlling other self-organizing systems.