Forming Long Term Teams to Exploit Synergies among Heterogeneous Agents

Abstract

In this work, we describe how agents can take advantage of synergies among each other and increase their efficiency at accomplishing tasks by working in teams. We present different team structures for heterogeneous agents, which range from static teams that are formed upfront and never change, to dynamic teams where agents can change teams as need arises, to teams that allow only some types of agents to be members. We also develop teaming strategies that are strongly domain specific for the RoboCup Rescue simulation environment. RoboCup Rescue is a simulated environment which is characterized by uncertainty in available information and by severely limited communications among agents. The tasks to be accomplished are saving civilians who are trapped in buildings and preventing fires from spreading in the city. The locations of civilians and fires are not known upfront and have to be discovered. The domain constraints limit the applicability of some popular team formation algorithms and require adaptive strategies. We measure the effectiveness of the various teaming strategies we propose. Our experimental results support the hypothesis that teaming improves performance, and that more specialized and knowledge rich teaming arrangements perform better.