DocumentCode
3157937
Title
A Study of Multiagent Reinforcement Learning based on Quantum Theory
Author
Xiangping, Meng ; Yuzhen, Pi ; Quande, Yuan ; Ying, Pan
Author_Institution
Dept. of Electr. Eng., Changchun Inst. of Technol., Changchun
Volume
2
fYear
2006
fDate
4-6 Oct. 2006
Firstpage
1990
Lastpage
1993
Abstract
In this paper, we present a novel multiagent reinforcement learning algorithm based on Q-learning and quantum theory. As in reinforcement learning algorithm, when the number of agents or/and agent´s action is large enough, all of the action selection methods will be failed: the speed of learning is decreased sharply, we try to combine the quantum theory with Q-learning, hoping that the problem will be resolved with our proposed.
Keywords
learning (artificial intelligence); multi-agent systems; quantum computing; Q-learning; multiagent reinforcement learning; quantum theory; reinforcement learning algorithm; Application software; Autonomous agents; Game theory; Learning; Optimal control; Quantum computing; Quantum mechanics; Space technology; Stochastic processes; Systems engineering and theory; Grover operator; Multiagent; Quantum algorithm; Reinforcement learning; Stochastic games;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Engineering in Systems Applications, IMACS Multiconference on
Conference_Location
Beijing
Print_ISBN
7-302-13922-9
Electronic_ISBN
7-900718-14-1
Type
conf
DOI
10.1109/CESA.2006.4281965
Filename
4281965
Link To Document