Decision-making for Multi-agent Industrial Systems

Distributed Decision-making in Disrupted Industrial Environments Using a Multi-agent Framework

Student: Mingjie Bi

The modern industrial environment is becoming more complex and dynamic, where varying uncertainties and disruptions could occur and highly impact the performance of manufacturing factories and supply chain networks. Conventional decision-making approaches lack the flexibility and agility to effectively handle disruptions. Enabled by current Artificial Intelligence (AI) techniques, multi-agent control has been proposed to conduct distributed decision-making to provide an agile response to disruptions. A multi-agent system consists of various autonomous agents, which are cyber representations of their associated physical objects (e.g., machine, supplier, etc.) and have their own knowledge and goals. Agents communicate and interact with each other to make high-level decisions for their associated physical objects. This project develops a model-based multi-agent framework to address risk management within an agile and resilient response to various unexpected industrial disruptions. The framework comprises model-based agents, heuristic-guided communication, and optimization-based decision-making, showcasing the improved flexibility, agility, and resiliency of the industrial systems.