TY - JOUR
T1 - Leading Ad Hoc agents in joint action settings with multiple teammates
AU - Agmon, Noa
AU - Stone, Peter
PY - 2012/1/1
Y1 - 2012/1/1
N2 - 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 the problem of leading iV-agent teams by an 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, thus its optimal strategy is to lead 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 other variations of the problem, including leading teams of agents where they base their actions on longer history of past observations, leading a team by more than one ad hoc agent, and leading a teammate while the ad hoc agent is uncertain of its behavior. Copyright © 2012, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
AB - 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 the problem of leading iV-agent teams by an 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, thus its optimal strategy is to lead 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 other variations of the problem, including leading teams of agents where they base their actions on longer history of past observations, leading a team by more than one ad hoc agent, and leading a teammate while the ad hoc agent is uncertain of its behavior. Copyright © 2012, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.
UR - http://www.scopus.com/inward/record.url?scp=84899454787&partnerID=8YFLogxK
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VL - 1
SP - 341
EP - 348
JO - Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems
JF - Proceedings of the 12th International Conference on Autonomous Agents and Multiagent Systems
ER -