Research on Collaborative Decision Making Mechanism for Helicopter Rescue Tasks Based on Intelligent Computing

In order to improve the collaborative decision-making efficiency of helicopter rescue missions in complex dynamic environments, a three-layer collaborative decision-making mechanism based on intelligent computing was constructed. Combining multi-agent system theory, deep reinforcement learning, and improved intelligent optimization algorithms, a multi-objective collaborative decision-making model and real-time strategy generation method were proposed. The study analyzed the resource, time, and spatial constraints of rescue missions, and designed simulation experiments to verify the effectiveness and robustness of the decision-making mechanism. The results indicate that the constructed collaborative decision-making mechanism is significantly superior to traditional methods in terms of task allocation efficiency, path optimization capability, and real-time system response, providing important support for intelligent emergency rescue systems.