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Home > chinese-english > "连续状态" in English

English translation for "连续状态"

continuous state
Example Sentences:
1.Hybrid dynamical system originated from the application of discrete event systems to supervising continuous state systems is discussed
摘要混合动态系统起因于离散事件系统用于监控连续状态系统的行为。
2.However , because coordination graph needs discrete state variant , it ca n ' t be applied in continuous state space such as robocup which communication condition is limited
但是协作图要求离散状态变量,所以无法直接应用到类似robocup这种通讯条件受到限制的连续状态空间。
3.The continuous state system is described by using abstract language method , and the discrete event plant model is attained by consistent partition of the space of continuous state system
用抽象语言方法描述连续状态系统,通过对连续状态系统空间的一致性分划,抽象出离散事件对象模型。
4.In contract to traditional finite time control algorithms based on non - continuous feedbacks , the finite time control algorithms based on continuous feedbacks are more suitable for application to control engineering
与基于非连续状态反馈的传统有限时间控制算法相比,基于连续状态反馈的有限时间控制算法更适合于控制工程应用。
5.The effective adhesion of permeable base and asphalt pavement , good residence of scouring property of mixture and good drainable property are benefit for undersurface of pavement and permeable base course to keep good successive contact condition
大孔隙水泥稳定碎石排水基层和沥青面层的有效联结、混合料本身良好的抗冲刷性能和良好的排水性能,有利于沥青下面层和排水基层的层间接触条件维持在连续状态
6.Supported by the national natural science foundation of china ( nsfc ) 2 , the research topic of this paper has been focused on reinforcement learning and its applications in mobile robot navigation . one part of the main contents in this paper is the generalization methods for reinforcement learning in solving markov decision problems with continuous states and actions . another part of the main contents is the applications of reinforcement learning methods in the optimization of the path tracking controllers and the autonomous navigation controllers for mobile robots
本文在国家自然科学基金项目“增强学习泛化方法研究及其在移动机器人导航中的应用”的资助下,以增强学习及其在移动机器人导航控制中的应用为研究内容,重点研究了增强学习在求解连续状态和行为空间markov决策问题时的泛化( generalization )方法,并针对移动机器人在未知环境中的自主导航和路径跟踪控制器的优化设计问题,研究了增强学习在上述领域中的应用。
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