DALI: A Decentralized, Agent-Based Approach for Adaptive Manufacturing Using Local Information

We study how decentralized multi-agent systems adapt on local data in dynamic environments. In this extension of our earlier work, we build on our original setting of a driverless transportation system for a manufacturing scenario with Autonomous Guided Vehicles (AGVs) to include not only disturbances, but also perception and communication errors that hinder the information sharing of agents. We analyze how well the decentralized MAS can correct these errors, where corrections come from, how the errors impact the performance, and consider the communication efficiency among the MAS population.