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Sponsored Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt Design Multi-Agent AI Systems Using MCP and A2A: Engineer your own Pyt

Author

Jing Jiang

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Open access 2026

ShellMean-MAPPO: A Conflict-Aware MARL Framework for Downlink Resource Allocation in Multi-Shell LEO Satellite Networks

This work proposes a structured multi-agent reinforcement learning (MARL) framework based on multi-agent proximal policy optimization (MAPPO), termed ShellMean-MAPPO, for downlink resource allocation with explicit conflict resolution, and demonstrates its advantages over representative MARL schemes in terms of scheduling performance and conflict mitigation.

Li Zhen, Qi-Hao Zhang, Qing-Zhi Meng et al. · 0 citations

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