Guest Editors
Dr. Kang Yang
Email: kyang73@g.ucla.edu
Affiliation: Electrical and Computer Engineering Department, University of California, Los Angeles, CA, United States
Homepage:
Research Interests: AI-enabled design and optimization of cyber-physical systems
Summary
Cyber-Physical Systems (CPS) represent a class of intelligent systems that seamlessly integrate sensing, computation, and actuation to interact with and control the physical world. The design and operation of modern CPS are marked by growing complexity, characterized by heterogeneous components, large-scale data flows, strict real-time constraints, and dynamic uncertain environments. Artificial Intelligence (AI) has become a transformative enabler, offering advanced methods to address these inherent challenges.
This Special Issue focuses on the application of advanced AI techniques to optimize the design and improve the autonomy and resilience of CPS. We welcome contributions that go beyond conventional control and networking approaches, focusing on how machine learning, deep learning, reinforcement learning, and related AI techniques can be leveraged for CPS to automate, enhance, and optimize their design, deployment, and adaptive management.
Topics of Interest:
· AI-assisted cross-layer co-design of hardware, software, and control in CPS.
· Reinforcement learning for real-time adaptive control and resource optimization in CPS.
· Federated and collaborative learning across distributed CPS.
· Self-organizing and self-optimizing behaviors in decentralized CPS.
· Intelligent operation and maintenance of CPS: anomaly detection, predictive maintenance, and fault resilience.
· Adversarial machine learning and defensive strategies in CPS.
Keywords
Artificial Intelligence (AI); Cyber-Physical Systems (CPS); System Design and Optimization
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