Robust and Scalable Coordination of Potential-Field Driven Agents

In this paper, we introduce a nature-inspired multi- agent system for the task domain of resource distribution in large storage facilities. The system is based on potential fields and swarm intelligence, in which straightforward path planning is integrated. We show both experimentally and theoretically that the system is adaptive, robust and scalable. Moreover, we show that the planning component helps to overcome common pitfalls for nature-inspired systems in the task assignment domain. We end this paper with a discussion of an additional requirement for multi-agent systems interacting with humans: functionality. More precisely, we argue that such systems must behave in a fair way to be functional. We illustrate how fairness can be measured and illustrate that our system behaves in a moderately fair manner.