Complex Systems and Artificial Intelligence

Dear Colleagues,

Due to the rapid development of algorithms, frameworks, hardware, networks, and the increased volume of data, artificial intelligence (AI) algorithms (e.g., deep learning, neural computing, biological computing, etc.) have been widely employed to solve problems in many complex systems. AI-based techniques and emerging new computing paradigms could extract sophisticated features and help us to address the practical problems that occur in complex systems more easily. For example, DNA computing—an emerging branch of biological computing—uses DNA, biochemistry, and molecular biology hardware to overcome the limitations of traditional electronic computing architecture in storing technologies, synthetic controllers and reaction networks, etc.

This Topic aims to highlight and present the latest developments in complex systems and artificial intelligence, addressing the challenge of how to apply advanced artificial intelligence algorithms, frameworks, and technologies to complex systems for a better world. Research fields could include industry, traffic, biology, agriculture, economy, environment, management, etc.

Contributions will focus on challenging issues in the field of complex systems and artificial intelligence technologies, frameworks, architectures, algorithms, and applications. Both theoretical and experimental contributions containing novel applications with new insights and findings in the field of complex systems and artificial intelligence are welcome. Review articles detailing the current state of the art are also encouraged. Topics of interest include, but are not limited to, the following:

• Complex evolutionary and adaptive systems;
• Self-organizing collective systems;
• AI-driven problem solving for complex systems;
• Machine learning for complex systems;
• Deep learning for complex systems;
• Neural computing for complex systems;
• Multi-agent for complex systems;
• Knowledge graph for complex systems;
• Data-driven AI for complex systems;
• Feature extraction and optimization;
• Multimodal feature fusion for complex systems;
• Biological computing for complex systems;
• AI in networks;
• AI and optimization problems;
• AI-based sensing, decision, and control for complex systems…

Prof. Dr. Qiang Zhang
Prof. Dr. Yifeng Zeng
Topic Editors