TY - GEN
T1 - Who to Blame? learning and control strategies with information asymmetry
AU - Liu, Changliu
AU - Zhang, Wenlong
AU - Tomizuka, Masayoshi
N1 - Publisher Copyright:
© 2016 American Automatic Control Council (AACC).
PY - 2016/7/28
Y1 - 2016/7/28
N2 - The rise of robot-robot interactions (RRI) is pushing for novel controller design techniques. Instead of using fixed control laws, robots should choose actions to minimize some cost functions specified by the designer. However, since the cost function of one robot may not be known to other robots (information asymmetry), special reasoning strategies are needed for multiple robots to learn to cooperate. Analysis shows that conventional learning and control strategies can lead to instability in a multi-agent system since the imperfection of other agents is not considered. In this paper, a new learning and control strategy that deals with interactions among imperfect agents is proposed. Analysis and simulation results show that the proposed strategy improves the performance of the system.
AB - The rise of robot-robot interactions (RRI) is pushing for novel controller design techniques. Instead of using fixed control laws, robots should choose actions to minimize some cost functions specified by the designer. However, since the cost function of one robot may not be known to other robots (information asymmetry), special reasoning strategies are needed for multiple robots to learn to cooperate. Analysis shows that conventional learning and control strategies can lead to instability in a multi-agent system since the imperfection of other agents is not considered. In this paper, a new learning and control strategy that deals with interactions among imperfect agents is proposed. Analysis and simulation results show that the proposed strategy improves the performance of the system.
UR - http://www.scopus.com/inward/record.url?scp=84992070803&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84992070803&partnerID=8YFLogxK
U2 - 10.1109/ACC.2016.7526122
DO - 10.1109/ACC.2016.7526122
M3 - Conference contribution
AN - SCOPUS:84992070803
T3 - Proceedings of the American Control Conference
SP - 4859
EP - 4864
BT - 2016 American Control Conference, ACC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 American Control Conference, ACC 2016
Y2 - 6 July 2016 through 8 July 2016
ER -