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Minghong Geng

2 accepted papers

2026

Scaling Up Cooperative Multi-Agent Reinforcement Learning Through Hierarchical Heterogeneous Modular Architectures

AAAI 2026technical

Multi-agent reinforcement learning enables sophisticated collaborative behaviors in autonomous systems, yet fundamental scalability barriers persist: existing methods struggle to coordinate large agent populations and face challenges with extended decision-making horizons. This research develops hie

Cited by 0SourcePDFScholar
2025

L2M2: A Hierarchical Framework Integrating Large Language Model and Multi-agent Reinforcement Learning

IJCAI 2025

Multi-agent reinforcement learning (MARL) has demonstrated remarkable success in collaborative tasks, yet faces significant challenges in scaling to complex scenarios requiring sustained planning and coordination across long horizons. While hierarchical approaches help decompose these tasks, they ty

Cited by 0SourcePDFScholar