TY - JOUR
T1 - Elevator Group Control Using Multiagent Task-Oriented Reinforcement Learning
AU - Kamal, M. A.S.
AU - Murata, Junichi
AU - Hirasawa, Kotaro
PY - 2005
Y1 - 2005
N2 - In this paper, a reinforcement learning method is proposed that optimizes passenger service in elevator group systems. Task-oriented reinforcement learning using multiple agents is applied in the control system in allocating immediate landing calls to the elevators and operating them intelligently in attaining better service in this stochastic dynamic domain. The proposed system shows better adaptive performance in different traffic profiles with faster convergence compared to the other learning elevator group control system.
AB - In this paper, a reinforcement learning method is proposed that optimizes passenger service in elevator group systems. Task-oriented reinforcement learning using multiple agents is applied in the control system in allocating immediate landing calls to the elevators and operating them intelligently in attaining better service in this stochastic dynamic domain. The proposed system shows better adaptive performance in different traffic profiles with faster convergence compared to the other learning elevator group control system.
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U2 - 10.1541/ieejeiss.125.1140
DO - 10.1541/ieejeiss.125.1140
M3 - Article
AN - SCOPUS:49649092578
SN - 0385-4221
VL - 125
SP - 1140
EP - 1146
JO - IEEJ Transactions on Electronics, Information and Systems
JF - IEEJ Transactions on Electronics, Information and Systems
IS - 7
ER -