论文主要研究了基于平均型强化学习算法的动态调度方法。
The thesis mainly focuses on the dynamic scheduling method based on the averaged rewards reinforcement learning algorithms.
本文提出了一种基于多智能体结构的车间层动态调度方法。
An approach to realize shop dynamic scheduling system based on multi agent architecture is proposed in this paper.
针对大型离散企业产品组装空间调度问题，提出了一种基于树搜索的动态调度方法。
This paper proposes a dynamic spatial scheduling approach based on tree-search to solve the assembling spatial scheduling problem in the large-sized discrete companies.
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