eXtreme-Ants : Ant Based Algorithm for Task Allocation in Extreme Teams

This paper addresses the problem of multiagent task allocation in extreme teams. An extreme team is composed by a large number of agents with overlapping functionality operating in dynamic environments with possible inter-task constraints. We present an approximate algorithm for task allocation in extreme teams, called eXtreme-Ants. The algorithm is inspired in the division of labor in social insects and in the process of recruitment for cooperative transport observed in ant colonies. The model of division of labor offers fast and efficient decision-making, while the recruitment ensures the allocation of constrained tasks that require simultaneous execution. We show that eXtreme-Ants outperforms other two algorithms regarding communication and computational effort.