Task allocation in multi-agent systems with swarm intelligence of social insects

Abstract

The Ant Task Allocation algorithm is proposed for task allocation in multi-agent systems, which is inspired by the swarm intelligence of social insects. The Ant Task Allocation algorithm is a variation of the Ant Colony Optimization, in which the task selection model of honeybees is adopted. In the simulation experiments, the Ant Task Allocation algorithm achieves efficient and reasonable task allocation in a random working environment. Moreover, when the working condition changes, the proposed algorithm implements effective and efficient task re-allocation. Experimental results indicate the adaptability and robustness of the Ant Task Allocation algorithm.