Existing task allocation algorithms generally do not consider the effects of task interaction, such as interference, but instead assume that tasks are independent. That assumption is often violated in multi-agent systems, e.g., in the case of cooperative mobile robots, where interaction effects can have a critical impact on performance. Modeling the effects of the interactions within a multi-agent system, the group dynamics, is difficult due to their complexity. The same complexity also makes it difficult to program, by hand, optimal solutions to multi-robot task allocation (MRTA) problems. We formalize the concept of group dynamics in the traditional framework of scheduling and show that task allocation in multi-agent systems with significant performance effects from the group dynamics is an NP-complete problem. We then present a simplified model of task allocation in multi-agent systems based on vacancy chains. A vacancy chain is a resource distribution process commonly found ...
Torbjørn S. Dahl, Maja J. Mataric, Gaurav S