Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling

About the authorSchirin Bär researched at the RWTH-Aachen University at the Institute for Information Management in Mechanical Engineering (IMA) on the optimization of production control of flexible manufacturing systems using reinforcement learning. As operations manager and previously as an engineer, she developed and evaluated the research results based on real systems.

Introduction.- Requirements for Production Scheduling in Flexible Manufacturing.- Reinforcement Learning as an Approach for Flexible Scheduling.-  Concept for Multi-Resources Flexible Job-Shop Scheduling.- Multi-Agent Approach for Reactive Scheduling in Flexible Manufacturing.- Empirical Evaluation of the Requirements.- Integration into a Flexible Manufacturing System.- Bibliography.