DocumentCode :
1887114
Title :
Emergence of adaptive behavior by chaotic neural networks
Author :
Suzuki, Ikuo ; Yokoi, Hiroshi ; Kakazu, Yukinori
Author_Institution :
Graduate Sch. of Eng., Hokkaido Univ., Japan
Volume :
1
fYear :
2003
fDate :
16-20 July 2003
Firstpage :
151
Abstract :
In this paper, we propose an emergent system in which an autonomous mobile robot can acquire environment oriented behavior. In the general robotic engineering, a system designer gave the model of environment and sensory-motor commands beforehand. However, we think that the autonomous robot has to be developed through the interaction between robot´s behavior and the environmental information by itself. So, we construct the controller for the autonomous robot to acquire the adaptive behavior with the chaotic neural networks (CNNs). Furthermore, we make use of the dynamic learning method (DLM) as an on-line learning method. The results of the computational experiments show the chaotic search of this network plays an important role for the acquisition of the adaptive behavior.
Keywords :
adaptive systems; chaos; emergent phenomena; learning (artificial intelligence); mobile robots; neural nets; adaptive behavior emergence; autonomous mobile robot; chaotic neural networks; dynamic learning method; emergent system; environment oriented behavior; general robotic engineering; on-line learning method; sensory-motor commands; Adaptive control; Cellular neural networks; Chaos; Design engineering; Learning systems; Mobile robots; Neural networks; Programmable control; Robot sensing systems; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence in Robotics and Automation, 2003. Proceedings. 2003 IEEE International Symposium on
Print_ISBN :
0-7803-7866-0
Type :
conf
DOI :
10.1109/CIRA.2003.1222080
Filename :
1222080
Link To Document :
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