咨询与建议

看过本文的还看了

相关文献

该作者的其他文献

文献详情 >Reinforcement Learning and App... 收藏

Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

反馈控制的强化学习和近似动态规划(丛书)

丛 书 名:IEEE Press Series on Computational Intelligence

版本说明:1

作     者:Frank L. Lewis Derong Liu 

I S B N:(纸本) 9781118104200 

出 版 社:IEEE 

出 版 年:2013年

页      数:633页

主 题 词:reinforcement learning and approximate dynamic programming for feedback control reinforcement learning adaptive control stochastic learning function approximators frank lewis derong liu cao busoniu Reinforcement learning approximate dynamic programming optimal control systems adaptive dynamic programming policy iteration value iteration ieee book ieee series ieee 

学科分类:080903[工学-微电子学与固体电子学] 0808[工学-电气工程] 0809[工学-电子科学与技术(可授工学、理学学位)] 08[工学] 0835[工学-软件工程] 0802[工学-机械工程] 080201[工学-机械制造及其自动化] 0812[工学-计算机科学与技术(可授工学、理学学位)] 

馆 藏 号:201409404...

摘      要:Reinforcement learning (RL) and adaptive dynamic programming (ADP) has been one of the most critical research fields in science and engineering for modern complex systems. This book describes the latest RL and ADP techniques for decision and control in human engineered systems, covering both single player decision and control and multi-player games. Edited by the pioneers of RL and ADP research, the book brings together ideas and methods from many fields and provides an important and timely guidance on controlling a wide variety of systems, such as robots, industrial processes, and economic decision-making.

实体馆藏
馆藏地名称 定位 索书号 条码号 文献状态
外文图书借阅室 查看 TP273/R367-2/X 020046366 可借

读者评论 与其他读者分享你的观点

用户名:未登录
我的评分