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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

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Marley Brown

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Open access 2026

Deep Reinforcement Learning for Adaptive Transportation Logistics Routing During Natural Disasters and Infrastructure Failures

An investigation of deep reinforcement learning for adaptive, real-time logistics routing under disaster conditions, culminating in a proposed graph-attention multi-agent proximal policy optimization architecture (GAT-MAPPO), which achieved the highest demand fulfillment rate and lowest mean delivery delay.

Oyinloluwa Sarah Ogunseye, Marley Brown, Yejide Eniola Dabiri · 0 citations

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