Click Here to Download: https://ouo.io/Xmx34CO Frontiers Of Intelligent Control And Information Processing By: Derong Liu Publisher: WSPC Print ISBN: 9789814616874, 9814616877 eText ISBN: 9789814616898, 9814616893 Pages: 480 Format: EPUB Available from $ 58.00 USD SKU 9789814616898 The current research and development in intelligent control and information processing have been driven increasingly by advancements made from fields outside the traditional control areas, into new frontiers of intelligent control and information processing so as to deal with ever more complex systems with ever growing size of data and complexity. As researches in intelligent control and information processing are taking on ever more complex problems, the control system as a nuclear to coordinate the activity within a system increasingly need to be equipped with the capability to analyze, and reason so as to make decision. This requires the support of cognitive components, and communication protocol to synchronize events within the system to operate in unison. In this review volume, we invited several well-known experts and active researchers from adaptive/approximate dynamic programming, reinforcement learning, machine learning, neural optimal control, networked systems, and cyber-physical systems, online concept drift detection, pattern recognition, to contribute their most recent achievements into the development of intelligent control systems, to share with the readers, how these inclusions helps to enhance the cognitive capability of future control systems in handling complex problems. This review volume encapsulates the state-of-art pioneering works in the development of intelligent control systems. Proposition and evocations of each solution is backed up with evidences from applications, could be used as references for the consideration of decision support and communication components required for today intelligent control systems. Contents: Dynamic Graphical Games: Online Adaptive Learning Solutions Using Approximate Dynamic Programming (Mohammed I Abouheaf & Frank L Lewis) Reinforcement-Learning-Based Online Learning Control for Discrete-Time Unknown Nonaffine Nonlinear Systems (Xiong Yang, Derong Liu, Qinglai Wei & Ding Wang) Experimental Studies on Data-Driven Heuristic Dynamic Programming for POMDP (Zhen Ni, Haibo He & Xiangnan Zhong) Online Reinforcement Learning for Continuous-State Systems (Yuanheng Zhu & Dongbin Zhao) Adaptive Iterative Learning Control of Robot Manipulators in the Presence of Environmental Constraints (Xiongxiong He, Zhenhua Qin & Xianqing Wu) Researchers in development of intelligent control systems with big data, as well as postgraduate students in adaptive control systems.
