Online reinforcement learning control by Bayesian inference
Xia, Zhongpu; Zhao, Dongbin; Dongbin Zhao
2016-08-08
发表期刊IET CONTROL THEORY AND APPLICATIONS
卷号10期号:12页码:1331-1338
文章类型Article
摘要Reinforcement learning offers a promising way for self-learning control of an unknown system, but it involves the issues of policy evaluation and exploration, especially in the domain of continuous state. In this study, these issues are addressed from the perspective of probability. It models the action value function as the latent variable of Gaussian process, while the reward as the observed variable. Then an online approach is proposed to update the action value function by Bayesian inference. Taking an advantage of the proposed framework, a prior knowledge can be incorporated into the action value function, and thus an efficient exploration strategy is presented. At last, the Bayesian-state-action-reward-state-action algorithm is tested on some benchmark problems and empirical results show its effectiveness.
关键词Learning Systems Bayes Methods Gaussian Processes Optimal Control Online Reinforcement Learning Control Bayesian Inference Self-learning Control Probability Action Value Function Gaussian Process Bayesian-state-action-reward-state-action Algorithm
WOS标题词Science & Technology ; Technology
DOI10.1049/iet-cta.2015.0669
关键词[WOS]AFFINE NONLINEAR-SYSTEMS ; FEEDBACK-CONTROL ; TIME-SYSTEMS ; ALGORITHM ; ITERATION
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China (NSFC)(61273136 ; 61573353 ; 61533017)
WOS研究方向Automation & Control Systems ; Engineering ; Instruments & Instrumentation
WOS类目Automation & Control Systems ; Engineering, Electrical & Electronic ; Instruments & Instrumentation
WOS记录号WOS:000381410000003
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被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11432
专题复杂系统管理与控制国家重点实验室_深度强化学习
通讯作者Dongbin Zhao
作者单位Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
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Xia, Zhongpu,Zhao, Dongbin,Dongbin Zhao. Online reinforcement learning control by Bayesian inference[J]. IET CONTROL THEORY AND APPLICATIONS,2016,10(12):1331-1338.
APA Xia, Zhongpu,Zhao, Dongbin,&Dongbin Zhao.(2016).Online reinforcement learning control by Bayesian inference.IET CONTROL THEORY AND APPLICATIONS,10(12),1331-1338.
MLA Xia, Zhongpu,et al."Online reinforcement learning control by Bayesian inference".IET CONTROL THEORY AND APPLICATIONS 10.12(2016):1331-1338.
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