Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling
Download or Read eBook Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling PDF written by Schirin Bär and published by Springer Nature. This book was released on 2022-10-01 with total page 163 pages. Available in PDF, EPUB and Kindle.
| Author | : Schirin Bär |
| Publisher | : Springer Nature |
| Total Pages | : 163 |
| Release | : 2022-10-01 |
| ISBN-10 | : 9783658391799 |
| ISBN-13 | : 3658391790 |
| Rating | : 4/5 (99 Downloads) |
Book Synopsis Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling by : Schirin Bär
Book excerpt: The production control of flexible manufacturing systems is a relevant component that must go along with the requirements of being flexible in terms of new product variants, new machine skills and reaction to unforeseen events during runtime. This work focuses on developing a reactive job-shop scheduling system for flexible and re-configurable manufacturing systems. Reinforcement Learning approaches are therefore investigated for the concept of multiple agents that control products including transportation and resource allocation.
