TY - GEN
T1 - Towards robust teams with many agents
AU - Kaminka, Gal A.
AU - Bowling, Michael
PY - 2002
Y1 - 2002
N2 - Agents in deployed multi-agent systems monitor other agents to coordinate and collaborate. However, as the number of agents monitored is scaled up, two key challenges arise: (i) the number of monitoring hypotheses to be considered can grow exponentially in the number of agents; and (ii) agents become physically and logically unconnected (unobservable) to their peers. This paper examines these challenges in teams of cooperating agents, focusing on a monitoring task that is of particular importance to robust teamwork: Detecting disagreements among team-members. We present YOYO, a highly scalable disagreement-detection algorithm which guarantees sound detection in time linear in the number of agents despite the exponential number of hypotheses. In addition, we present new upper bounds for the number of agents that must be monitored in a team to guarantee disagreement detection. Both YOYO and the new bounds are explored analytically and empirically in thousands of monitoring problems, scaled to thousands of agents.
AB - Agents in deployed multi-agent systems monitor other agents to coordinate and collaborate. However, as the number of agents monitored is scaled up, two key challenges arise: (i) the number of monitoring hypotheses to be considered can grow exponentially in the number of agents; and (ii) agents become physically and logically unconnected (unobservable) to their peers. This paper examines these challenges in teams of cooperating agents, focusing on a monitoring task that is of particular importance to robust teamwork: Detecting disagreements among team-members. We present YOYO, a highly scalable disagreement-detection algorithm which guarantees sound detection in time linear in the number of agents despite the exponential number of hypotheses. In addition, we present new upper bounds for the number of agents that must be monitored in a team to guarantee disagreement detection. Both YOYO and the new bounds are explored analytically and empirically in thousands of monitoring problems, scaled to thousands of agents.
UR - http://www.scopus.com/inward/record.url?scp=0036355176&partnerID=8YFLogxK
U2 - 10.1145/544915.544916
DO - 10.1145/544915.544916
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AN - SCOPUS:0036355176
SN - 9781581134803
T3 - Proceedings of the International Conference on Autonomous Agents
SP - 729
EP - 736
BT - Proceedings of the International Conference on Autonomous Agents
PB - Association for Computing Machinery (ACM)
T2 - Proceedings of the 1st International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS 2002
Y2 - 15 July 2002 through 19 July 2002
ER -