Reinforcement Learning and Approximate Dynamic Programming for Feedback Control

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.