GPEvac: GNN-Based PPO for Adaptive Evacuation Routing During Shooting Events
Leveraging reinforcement learning and graph neural networks to optimize life-saving evacuation routes.
The sharp increase in mass shootings underscores an urgent need for systems that guide victims to safety in real time. An effective evacuation system must minimize threat exposure while also accounting for adversarial uncertainty and crowding dynamics. Current methods in the lite...
ArXiv CS.AI
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GPEvac represents a critical shift in public safety technology by leveraging reinforcement learning to navigate the chaotic, high-stakes environment of active threat scenarios. By integrating graph neural networks, the system can dynamically optimize evacuation paths to bypass threats while preventing dangerous bottleneck congestion.
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