Mingcheng Zhang · Nanyang Technological University

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Works5 from public data

TitleCited by

Tactical conflict resolution in urban airspace for unmanned aerial vehicles operations using attention-based deep reinforcement learning
Mingcheng Zhang, Chao Yan, Wei Dai, Xiaojia Xiang, Kin Huat Low
Green Energy and Intelligent Transportation · 2023
37
Real-Time Avoidance of Obstacles and Emergent Geo-Fences for Urban Air Mobility Using Deep Reinforcement Learning
Mingcheng Zhang, Bizhao Pang, Chao Yan, Mir Feroskhan, Chen Lv
IEEE Transactions on Intelligent Transportation Systems · 2025
6
Decentralized Deep Reinforcement Learning for Cooperative Multi-Agent Flight Trajectory Planning in Adverse Weather
Bizhao Pang, Xinting Hu, Mingcheng Zhang, Sameer Alam, Guglielmo Lulli
Adaptive Agents and Multi-Agents Systems · 2025
2
MAF-DAC: Constrained Multi-Agent Reinforcement Learning With Multi-Head Action Filtering for Safe Aircraft Trajectory Planning
Bizhao Pang, Mingcheng Zhang, Xinting Hu, Sameer Alam, Guglielmo Lulli
IEEE Transactions on Intelligent Transportation Systems · 2026
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Constrained Multi-Agent Reinforcement Learning with MAF-Net for Safe Trajectory Planning
Bizhao Pang, Mingcheng Zhang, Xinting Hu, Thinh Pham, Sameer Alam, Guglielmo Lulli
Proceedings of the 25th International Conference on Autonomous Agents and Multiagent Systems · 2026
This work proposes IDDPG-MAF, which integrates Independent Deep Deterministic Policy Gradient with a pre-trained Multi-head Action Filter Network (MAF-Net), and enables scalable learning, while MAF-Net acts as a differentiable safety filter that masks unsafe actions and penalizes suboptimal behaviors.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.

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