Yueqi Hou
Papers
2
Total Citations
31
H-Index
2
About
Dr. Yueqi Hou is a leading researcher in autonomous systems and artificial intelligence, with a focus on decision-making for unmanned combat aerial vehicles (UCAVs) and deep reinforcement learning (DRL) applications. Their most cited work, a 2023 study on hierarchical decision-making for multiple UCAVs in autonomous confrontation (22 citations), addresses the critical challenge of dynamic, complex air combat scenarios. By proposing a rule-based framework that enhances interpretability over black-box AI methods, Hou provides a practical solution for real-time tactical coordination. Additionally, their comprehensive review of DRL methods and military applications (9 citations) surveys breakthroughs in robotic control and game strategy, highlighting DRL’s transformative potential for defense technologies. With a growing citation impact, Hou’s contributions bridge the gap between theoretical AI and operational military systems, offering interpretable, scalable frameworks that advance autonomous decision-making under uncertainty. Their work is essential reading for researchers and engineers developing next-generation intelligent systems for high-stakes environments.
Research Focus
Key Achievements
Top Papers
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