This paper proposed an adaptive A* Hybrid algorithm combining the advantages of ant colony and A* algorithm. Improvements of the traditional ant-colony algorithm was suggested, and the Target Evaluation Factor based on global dynamic information was introduced to promote the performance of ant path decision. In additional, an adaptive pheromone updating strategy was designed to balance and speed up the convergence rate. Test results showed that this algorithm can effectively guide agents to get an optimal path to ensure the efficient completion of tasks.

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