강화학습기법의 동적일정계획에의 적용가능성에 대한 소고
- Issued Date
- 2017
- Abstract
- The ability to dynamically reschedule jobs is core of flexible manufacturing system. Reinforcement learning, a machine learning approach undergoing development in various control systems, offers advantages in dynamic environments. This paper presents a feasibility study on the reinforcement learning for a dynamic scheduling problem.
- Alternative Title
- Feasibility Study on the Reinforcement Learning for a Dynamic Scheduling Problem
- Alternative Author(s)
- Jangha Kang
- Publisher
- 조선대학교 공학기술연구원
- Type
- Research Laboratory
- ISSN
- 2005-3142
- URI
- https://oak.chosun.ac.kr/handle/2020.oak/19263
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- Appears in Collections:
- 2017 > Vol 10, No 4
- Files in This Item:
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