Exploring Auction Mechanisms for Role Assignment in Teams of Autonomous Robots

We are exploring the use of auction mechanisms to assign roles within a team of agents operating in a dynamic environment. Depending on the degree of collaboration between the agents and the specific auction policies employed, we can obtain varying combinations of role assignments that can affect both the speed and the quality of task execution. In order to examine this extremely large set of combinations, we have developed a theoretical framework and an environment in which to experiment and evaluate the various options in policies and levels of collaboration. This paper describes our framework and experimental environment. We present results from examining a set of representative policies within our test domain — a high-level simulation of the RoboCup four-legged league soccer environment.