Adaptive Dynamic Programming and Control Application in Intelligent Systems

Dear Colleagues,

Adaptive dynamic programming (ADP) affords a methodology for learning optimal control actions online in real time based on system performance without necessarily knowing the system dynamics. It successfully combines the theories of neural networks, adaptive evaluation design, reinforcement learning and classical dynamic programming, effectively avoids the “curse of dimensionality”, and receives much attention and research. As a result, recent years have witnessed a tremendous growth in its application in intelligent systems, such as robotic unmanned vehicles. The aim of the proposed Special Issue is to introduce the latest research results on adaptive dynamic programming and control applications in intelligent systems, including ADP for optimal regulation, ADP for game theory, ADP for cooperative control, etc. This Special Issue provides an opportunity for both academic researchers, particularly in the systems and control community, and the automotive industry to acquire frontier knowledge on ADP technologies.

This Special Issue aims to provide up-to-date research concepts, theoretical findings, and practical solutions that could help advance ADP technologies. Topics of interest include, but are not limited to, the following:

• ADP-based intelligent control methods;
• Deep ADP technology;
• ADP for optimal regulation problems;
• ADP for game theory;
• ADP for large-scale systems;
• ADP for multi-agent systems;

Dr. Pingli Lu
Dr. Weinan Gao
Guest Editors

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