Papers
5
Total Citations
21
H-Index
4
About
Siming Liu is a researcher at the forefront of multi-agent robotics and artificial intelligence, with a core focus on enabling intelligent collaboration among autonomous systems. Their work addresses the fundamental challenge of how teams of robots can efficiently cooperate in complex, real-world environments. Liu’s major contributions lie in developing novel frameworks for multi-agent reinforcement learning (MARL), including a semi-centralized approach that leverages "awareness maps" to improve coordination, and a method for information sharing among cooperative robots. In the domain of automated infrastructure inspection, Liu pioneered the use of genetic algorithms to solve the Min-Max k Windy Chinese Postman Problem, creating balanced and efficient routing strategies for teams of robots inspecting steel truss bridges. This work has direct applications in civil engineering and infrastructure maintenance. Additionally, Liu has made notable contributions to artificial intelligence in gaming, evolving tactical control strategies for real-time strategy (RTS) games through multi-objective, cooperative co-evolutionary algorithms. With multiple papers accumulating citations and spanning from 2019 to 2025, Liu’s research is establishing a strong foundation for the next generation of collaborative autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 3Multi-objective cooperative co-evolution of micro for RTS games5 citations · 2019
- 4Comparing Three Approaches to Micro in RTS Games4 citations · 2019
- 5