Handling coordination failures in large-scale multi-agent systems

Agents monitor other agents to coordinate and collaborate robustly. The goals of such monitoring include detection of coordination failures. However, as the number of monitored agents is scaled up, two key challenges arise: (i) Agents become physically and logically unconnected (unobservable) to their peers; and (ii) the number of possible coordination failures grows exponentially, with all potential interactions. This paper examines these challenges in teams of cooperating agents. We provide a brief survey of the evolution of two key approaches to handling coordination failures in large-scale teams: Restricting the number of agents that must be monitored, and using model-based rather than fault-based detection methods. We focus on a monitoring task that is of particular importance to robust teamwork: detecting disagreements among team-members.