DocumentCode
3352649
Title
Experience based learning in policy control of multiagent system
Author
Damba, Ariuna ; Watanabe, Shigeyoshi
Author_Institution
Grad. Sch. of Electro-Commun., Univ. of Electro-Commun., Chofu
fYear
2008
fDate
21-24 Sept. 2008
Firstpage
335
Lastpage
340
Abstract
In this paper a method of simulated learning of policy control is proposed for dynamic multiagent system, where agentpsilas decision mechanism is represented as a function of agentpsilas past experience. The system of homogeneous agents with different sensor input and effector output is considered.
Keywords
learning (artificial intelligence); multi-agent systems; optimal control; experience based learning; multiagent system; policy control; Adaptation model; Artificial intelligence; Control system synthesis; Control systems; Decision making; History; Learning; Monte Carlo methods; Multiagent systems; Power system modeling; Monte Carlo Approach; Multi-vehicle Simulation; Multiagent System; Optimal Control; Reinforcement Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Cybernetics and Intelligent Systems, 2008 IEEE Conference on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-1673-8
Electronic_ISBN
978-1-4244-1674-5
Type
conf
DOI
10.1109/ICCIS.2008.4670964
Filename
4670964
Link To Document