The scale of Internet-connected systems has increased considerably, and these systems are
being exposed to cyberattacks more than ever. The complexity and dynamics of …

The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices
around the world, where the IoT devices collect and share information to reflect status of the …

Due to the recent progress in Deep Neural Networks, Reinforcement Learning (RL) has
become one of the most important and useful technology. It is a learning method where a …

This paper considers the design of optimal resource allocation policies in wireless
communication systems, which are generically modeled as a functional optimization …

This work studies the state estimation problem for nonlinear uncertain systems over a
shared communication channel. We transform the original system into an extended state …

Wireless networked control systems (WNCSs) provide a key enabling technique for
Industrial Internet of Things (IIoT). However, in the literature of WNCSs, most of the research …

Reconfigurable wireless network can flexibly provide efficient spectrum access service and
keep stable operation in highly dynamic environment. In this paper, a primary-prioritized …

Whittle index policy is a powerful tool to obtain asymptotically optimal solutions for the
notoriously intractable problem of restless bandits. However, finding the Whittle indices …

Soft actor-critic (SAC) is an off-policy actor-critic (AC) reinforcement learning (RL) algorithm,
essentially based on entropy regularization. SAC trains a policy by maximizing the trade-off …

In this paper, we focus on the tracking problem of a dual-arm robot (DAR) with prescribed
performance and unknown input backlash-like hysteresis. Considering this problem …