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cs.AI2026
Safe and Generalizable Hierarchical Multi-Agent RL via Constraint Manifold Control
Zihao Guo, Jianing Zhao, Ling Li +3
Multi-agent systems are widely used in safety-critical applications that require coordinated behavior under strict safety constraints. Existing approaches face a fundamental trade-…
cs.AI2024★ 1 cited
Multi-Agent Reinforcement Learning for Autonomous Driving: A Survey
Ruiqi Zhang, Jing Hou, Florian Walter +7
Reinforcement Learning (RL) is a potent tool for sequential decision-making and has achieved performance surpassing human capabilities across many challenging real-world tasks. As…