TY - GEN
T1 - Compositionality of Linearly Solvable Optimal Control in Networked Multi-Agent Systems
AU - Song, Lin
AU - Wan, Neng
AU - Gahlawat, Aditya
AU - Hovakimyan, Naira
AU - Theodorou, Evangelos A.
N1 - Publisher Copyright:
© 2021 American Automatic Control Council.
PY - 2021/5/25
Y1 - 2021/5/25
N2 - In this paper, we discuss the methodology of generalizing the optimal control law from learned component tasks to unlearned composite tasks on Multi-Agent Systems (MASs), by using the linearity composition principle of linearly solvable optimal control (LSOC) problems. The proposed approach achieves both the compositionality and optimality of control actions simultaneously within the cooperative MAS framework in both discrete and continuous-time in a sample-efficient manner, which reduces the burden of re-computation of the optimal control solutions for the new task on the MASs. We investigate the application of the proposed approach on the MAS with coordination between agents. The experiments show feasible results in investigated scenarios, including both discrete and continuous dynamical systems for task generalization without resampling.
AB - In this paper, we discuss the methodology of generalizing the optimal control law from learned component tasks to unlearned composite tasks on Multi-Agent Systems (MASs), by using the linearity composition principle of linearly solvable optimal control (LSOC) problems. The proposed approach achieves both the compositionality and optimality of control actions simultaneously within the cooperative MAS framework in both discrete and continuous-time in a sample-efficient manner, which reduces the burden of re-computation of the optimal control solutions for the new task on the MASs. We investigate the application of the proposed approach on the MAS with coordination between agents. The experiments show feasible results in investigated scenarios, including both discrete and continuous dynamical systems for task generalization without resampling.
UR - http://www.scopus.com/inward/record.url?scp=85111916534&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85111916534&partnerID=8YFLogxK
U2 - 10.23919/ACC50511.2021.9483210
DO - 10.23919/ACC50511.2021.9483210
M3 - Conference contribution
AN - SCOPUS:85111916534
T3 - Proceedings of the American Control Conference
SP - 1334
EP - 1339
BT - 2021 American Control Conference, ACC 2021
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 American Control Conference, ACC 2021
Y2 - 25 May 2021 through 28 May 2021
ER -