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Multi-agent reinforcement learning for autonomous emergency medical dispatch on wildfire-degraded road networks. Each vehicle agent keeps a private belief over road passability, reconciles evidence with peers when communication allows, and learns route-level exploration under triage-specific survival-risk budgets.
Multi-agent reinforcement learning for autonomous emergency medical dispatch on wildfire-degraded road networks. Each vehicle agent keeps a private belief over road passability, reconciles evidence with peers when communication allows, and learns route-level exploration under triage-specific survival-risk budgets.
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