From Chaos to Commerce: Practical Issues and Research Opportunities in the Nonlinear Dynamics of Decentralized Manufacturing Systems

Many potential applications for artificial intelligence (AI) in manufacturing extend classical AI in two ways. First, they go beyond modeling a single decision-maker to incorporate the interactions of multiple “agents.” Second, instead of fitting a “problem solving” rubric that seeks to reach achievement goals, they are more aptly cast as “going concerns” that support maintenance goals in the face of continual disruption. The first extension is the focus of active research in multi-agent systems (MAS), with which the IMS community has established effective ties. This paper proposes that the second extension can benefit from the use of concepts from dynamical systems theory (informally, “chaos theory”). This field provides useful metaphors for discussing going concerns. Its promise goes further than metaphor, for multi-agent systems are actually dynamical systems, whose effective design, monitoring, and control requires application of techniques developed in dynamical systems. Thus researchers and developers who are exploring and deploying MAS in manufacturing must give careful attention to the distinctive challenges and unique opportunities of dynamical systems theory.