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What is Heterogeneous Multi-Agent Task Allocation about?
This research article presents a novel approach for heterogeneous multi-agent task allocation using a Graph-based Heterogeneous Neural Network Ant Colony Optimization (GHNN-ACO) algorithm. The proposed method effectively combines graph neural networks with ant colony optimization to enhance task assignment efficiency among diverse agents like drones, unmanned ships, and vehicles, achieving a high accuracy rate of 95.31%. This innovative framework aims to improve performance in emergency response scenarios a
- Author
- huyixiang01
- Language
- EN