论文标题
纺织制造过程中基于学习的基于学习的决策支持系统
A reinforcement learning based decision support system in textile manufacturing process
论文作者
论文摘要
本文在纺织制造过程中介绍了基于增强学习的决策支持系统。讨论了颜色褪色臭氧化的解决方案优化问题，并将其设置为马尔可夫决策过程（MDP），以元组{s，a，p，r}表示。 Q学习用于通过累积奖励R来培训与设置环境的互动。根据申请结果，发现所提出的MDP模型很好地表达了本文讨论的纺织制造过程的优化问题，因此使用加固学习来支持该部门的决策，并证明了该领域的证明是适用于有希望的前景。
This paper introduced a reinforcement learning based decision support system in textile manufacturing process. A solution optimization problem of color fading ozonation is discussed and set up as a Markov Decision Process (MDP) in terms of tuple {S, A, P, R}. Q-learning is used to train an agent in the interaction with the setup environment by accumulating the reward R. According to the application result, it is found that the proposed MDP model has well expressed the optimization problem of textile manufacturing process discussed in this paper, therefore the use of reinforcement learning to support decision making in this sector is conducted and proven that is applicable with promising prospects.
