Artificial Intelligence of Things (AIoT) is an emerging frontier based on the deep fusion of
Internet of Things (IoT) and Artificial Intelligence (AI) technologies. The fundamental goal of …

In the paradigm of ubiquitous edge computing, with those advantages, eg, high mobility, fast
response, flexibility and controllability, and low cost of use, Unmanned Aerial Vehicles …

The quality of the video stream is key to neural network-based video analytics. However, low-
quality video is inevitably collected by existing surveillance systems because of poor quality …

多智能体强化学习作为博弈论, 控制论和多智能体学习的交叉研究领域, 是多智能体系统研究中
的前沿方向, 赋予了智能体在动态多维的复杂环境中通过交互和决策完成多样化任务的能力 …

The increasing demands for system complexity and robustness have prompted the
integration of temporal logic into Multi-Agent Reinforcement Learning (MARL) to address …

The quality of the video stream is the key to neural network-based video analytics. However,
low-quality video is inevitably collected by existing surveillance systems because of poor …

We provide a customizable environment based on Deep Reinforcement Learning (DRL)
strategies for handling cooperative multi-UAV (Unmanned Aerial Vehicles) scenarios when …

Learning to communicate (L2C) involves learning how, when, and with whom to
communicate to enhance cooperation among agents under limited bandwidth. However …

Action delay is very common in practical applications and can significantly impact the
effectiveness of reinforcement learning, especially in multi-agent scenarios, due to the lag in …

This paper investigates the state synchronization control problem of a teleoperation system
for actuators based on deep reinforcement learning, taking into account input saturation …