AAAI Publications, Workshops at the Twenty-Fifth AAAI Conference on Artificial Intelligence

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Leading Multiple Ad Hoc Teammates in Joint Action Settings
Noa Agmon, Peter Stone

Last modified: 2011-08-24

Abstract


The growing use of autonomous agents in practice may require agents to cooperate as a team in situations where they have limited prior knowledge about one another, cannot communicate directly, or do not share the same world models. These situations raise the need to design ad hoc team members, i.e., agents that will be able to cooperate without coordination in order to reach an optimal team behavior. This paper considers problem of leading N-agent teams by a single agent toward their optimal joint utility, where the agents compute their next actions based only on their most recent observations of their teammates' actions. We show that compared to previous results in two-agent teams, in larger teams the agent might not be able to lead the team to the action with maximal joint utility. In these cases, the agent's optimal strategy leads the team to the best possible reachable cycle of joint actions. We describe a graphical model of the problem and a polynomial time algorithm for solving it. We then consider the problem of leading teams where the agents' base their actions on a longer history of past observations, showing that the an upper bound computation time exponential in the memory size is very likely to be tight.

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