Balancing automated behavior and human control in multi-agent systems: a case study in RoboFlag

Abstract

Many potential robotic applications require operation in a highly dynamic environments and, in multi-agent systems, some degree of coordination between robots. Often it becomes necessary to include an element of human control in order to compensate for limitations in the automated reasoning available to the agents. This paper focuses on how one might include a human operator in the feedback loop of a multi-agent system, where the agent to human ratio is greater than one. Using the RoboFlag environment as a test-bed, we have implemented various levels of human interaction ranging from the most basic motion control to high-level behavior assignments. Evaluating our system in real time competition has shown that multiple levels of interaction are necessary for successful operation. Because the agent to human ratio is relatively high, it becomes difficult for the human to maintain low-level control of all the robots, but in critical or novel situations higher-level automated intelligence must be circumvented by the human.