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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling

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

Bär, Schirin

Paperback

Business GeneralTechnology & EngineeringGeneral Computers

ISBN10: 3658391782
ISBN13: 9783658391782
Publisher: Springer Vieweg
Published: Oct 2 2022
Pages: 148
Weight: 0.47
Height: 0.37 Width: 5.83 Depth: 8.27
Language: English
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.

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