Learning-Enabled Intelligent Decision-Making and Safe Control for Autonomous Systems

Autonomous systems including mobile robots, intelligent connected vehicles, unmanned aerial vehicles and multi-agent systems, are being increasingly applied in intelligent transportation, advanced manufacturing, logistics, and other emerging fields. However, operating in complex and dynamic environments, autonomous systems face various challenges, such as system uncertainties, communication constraints, component faults, and cyber-attacks, which impose higher requirements on intelligent decision-making, safe operation, and reliable control. In recent years, the rapid development of reinforcement learning, adaptive dynamic programming, artificial intelligence, and data-driven control methods has provided new theoretical foundations and technical approaches for enhancing the decision-making capability, adaptability, and safety performance of autonomous systems.

This special session aims to bring together researchers and practitioners from related fields to discuss the latest theoretical advances, key technologies, and engineering applications in learning-enabled intelligent decision-making and safe control for autonomous systems. The session focuses on emerging research topics, including intelligent learning, autonomous decision-making, safe control, cooperative control, and applications of autonomous systems.

移动机器人、智能网联汽车、无人机及多智能体系统等自主系统，正广泛应用于智能交通、先进制造、物流运输等领域。然而，在复杂动态环境下，自主系统面临系统不确定性、通信约束、部件故障及网络攻击等多重挑战，对其智能决策、安全运行与可靠控制能力提出了更高要求。近年来，强化学习、自适应动态规划、人工智能及数据驱动控制等学习方法的快速发展，为提升自主系统的决策自主性、环境适应性与控制安全性提供了新的理论基础与技术支撑。

本专题旨在汇聚国内外相关领域专家学者，围绕学习赋能的自主系统智能决策与安全控制，交流最新理论成果、关键技术及工程应用进展，重点关注智能学习、自主决策、安全控制、协同控制以及自主系统应用等前沿研究方向。