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This book offers a thorough introduction to the basics and scientific and technological innovations involved in the modern study of reinforcement-learning-based feedback control. The authors address a wide variety of systems including work on nonlinear, networked, multi-agent and multi-player systems.A concise description of classical reinforcement learning (RL), the basics of optimal control with dynamic programming and network control architectures, and a brief introduction to typical algorithms build the foundation for the remainder of the book. Extensive research on data-driven robust...

With the increasing popularization of personal hand-held mobile devices, more people use them to establish network connectivity and to query and share data among themselves in the absence of network infrastructure, creating mobile social networks (MSNet). Since users are only intermittently connected to MSNets, user mobility should be exploited to bridge network partitions and forward data. Currently, data route/forward approaches for such intermittently connected networks are commonly "store-carry-and-forward" schemes, which exploit the physical user movements to carry data around the...

A lot of digital ink has been spilled on "big data" over the past few years. Most of this surge owes its origin to the various types of unstructured data in the wild, among which the proliferation of text-heavy data is particularly overwhelming, attributed to the daily use of web documents, business reviews, news, social posts, etc., by so many people worldwide.A core challenge presents itself: How can one efficiently and effectively turn massive, unstructured text into structured representation so as to further lay the foundation for many other downstream text mining applications? In...