Papers
2
Total Citations
63
H-Index
2
About
Zijie Guo is a researcher specializing in intelligent control systems, multiagent coordination, and reinforcement learning-based optimization. His work focuses on developing sophisticated control frameworks for multiagent systems (MAS), particularly addressing real-world challenges such as external disturbances, output constraints, and input limitations that complicate cooperative behavior among networked agents. Guo's most recognized contribution, "Adaptive-Critic-Based Event-Triggered Intelligent Cooperative Control for a Class of Second-Order Constrained Multiagent Systems" (2022), has accumulated 58 citations and demonstrates his expertise in combining adaptive critic architectures with event-triggered mechanisms to achieve efficient, constraint-aware cooperative control. This work is notable for its handling of asymmetric and time-varying constraint ranges — a practically significant advancement over more idealized prior approaches. His more recent work on integral reinforcement learning for optimal containment control (2024) extends his research into partially unknown nonlinear systems, reflecting a growing interest in data-driven, model-free optimization strategies. Together, these contributions highlight Guo's commitment to bridging theoretical rigor with practical applicability in distributed intelligent systems. His research is particularly relevant for students and engineers working at the intersection of control theory, artificial intelligence, and multi-robot coordination.
Research Focus
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Top Papers
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