Self-Organizing Multi-Agent Systems for the Control of Complex Systems

Because of the law of requisite variety, designing a controller for complex systems implies designing a complex system. In software engineering, usual top-down approaches become inadequate to design such systems. The Adaptive Multi-Agent Systems (AMAS) approach relies on the cooperative self-organization of autonomous micro-level agents to tackle macro-level complexity. This bottom-up approach provides adaptive, scalable, and robust systems. This paper presents a complex system controller that has been designed following this approach, and shows results obtained with the automatic tuning of a real internal combustion engine