Enhancing Natural Disaster Response Networks with Advanced Graph-based Rescue Simulation

The project aims to develop advanced simulation models for natural disaster response by incorporating AI and graph-based algorithms, significantly improving decision-making capabilities, resource management, and coordination efficiency of simulated rescue agents during disaster scenarios. Expected outcomes include the development of robust and flexible pathfinding algorithms for dynamic disaster environments, a comprehensive suite of graph-based algorithms for simulation, and an adaptive learning framework that improves agent performance over time. These innovations will boost collaboration among emergency teams like police and firefighters, improving response strategies with better simulations. Enhanced accuracy and user-friendly tools will help save lives and streamline decision-making during disasters.