Zhenduo Meng | Machine Learning | Best Researcher Award
Inner Mongolia University, China
Zhenduo Meng is a graduate student pursuing his M.Sc. in Electronic Information Engineering at the School of Electronic Information Engineering, Inner Mongolia University, with a strong academic foundation built during his B.Eng. studies in Automation at Guangxi University. His research primarily focuses on multi-agent reinforcement learning (MARL), deep reinforcement learning, cooperative control of multi-agent systems, and the broader applications of artificial intelligence in intelligent decision-making. He has actively participated in several research projects, where he contributed to the development of algorithms integrating attention mechanisms and value decomposition methods to improve collaboration efficiency in MARL environments. Recently, his research work, “DDWCN: A Dual-Stream Dynamic Strategy Modeling Network for Multi-Agent Elastic Collaboration,” was accepted for publication in Applied Sciences (2025), highlighting his innovative contributions in the field. Despite being at the early stage of his academic journey, his scholarly output includes 2 documents, and his current citation count stands at zero, reflecting the fresh and emerging nature of his research profile. His h-index is also recorded as zero, consistent with his recent entry into the publication landscape. Proficient in Python, MATLAB, PyTorch, and TensorFlow, along with strong command of both Chinese and English, Meng demonstrates promising potential for impactful contributions in intelligent systems research.
Profile: Scopus
Featured Publications
Meng, Z., Na, X., Wang, T., Liu, J., & Wang, W. (2025). DDWCN: A dual-stream dynamic strategy modeling network for multi-agent elastic collaboration.
Wang, T., Na, X., Nie, Y., Liu, J., Wang, W., & Meng, Z. (2025). Parallel task offloading and trajectory optimization for UAV-assisted mobile edge computing via hierarchical reinforcement learning. Drones, 9(2),