DocumentCode :
2522771
Title :
Learning cooperative object pushing with variable contact point
Author :
Aminaiee, Abdol Hossein ; Ahmadabadi, Majid Nili
Author_Institution :
Tehran Univ., Tehran
fYear :
2007
fDate :
4-7 Sept. 2007
Firstpage :
1
Lastpage :
6
Abstract :
Learning in multi-agent environments where each agent´s action directly affects other agents would be an important matter and a complicated task. To reduce the learning time and simplifying the learning process, it is suitable to learn individual skills and then provide cooperation and coordination utilizing the learned individual skills. In the approach proposed in this paper, agents benefit from their individual knowledge obtained in the individual learning phase to cooperate with other agents. Cooperative object pushing system is used as a testbed to our proposed method where cooperation and coordination between agents are needed in these systems. Agents independently learn to push the object to the target by using the proposed fuzzy reinforcement learning method. Agents attain their cooperative behaviors properly making use of the coded knowledge in the Q-table. Simulation and experimental results show that by interpreting the knowledge in the Q-table, agents can achieve high level behaviors with a high degree of cooperation.
Keywords :
learning (artificial intelligence); mobile robots; multi-agent systems; cooperative object pushing system; fuzzy reinforcement learning method; mobile robot; multiagent environment; variable contact point; Artificial intelligence; Friction; Gravity; Intelligent agent; Intelligent robots; Learning; Mobile robots; Process control; Protocols; Robot kinematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced intelligent mechatronics, 2007 IEEE/ASME international conference on
Conference_Location :
Zurich
Print_ISBN :
978-1-4244-1263-1
Electronic_ISBN :
978-1-4244-1264-8
Type :
conf
DOI :
10.1109/AIM.2007.4412554
Filename :
4412554
Link To Document :
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