NDLI: Evolutionary construction of behavior arbitration mechanisms based on dynamically-rearranging neural networks

Content Provider	IEEE Xplore Digital Library
Author	Nakamura, H. Ishiguro, A. Uchilkawa, Y.
Copyright Year	2000
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Nagoya Univ., Japan (Nakamura, H.)
Abstract	Recently, the evolutionary robotics (ER) approach has been attracting lots of concern in the fields of robotics and artificial life, since it can automatically synthesize controllers by taking the embodiment and the interaction dynamics between the robot and its environment. However, the ER approach still has serious problems that have to be solved. In this study, we particularly focus on one of the critical problems in the ER: plasticity vs. stability dilemma. In order to alleviate this problem, we investigate the effectiveness of the dynamically-rearranging neural networks by taking a peg-collecting task, which requires appropriate sequence of behavior to accomplish the task, as a practical example.
Starting Page	158
Ending Page	165
File Size	718376
Page Count	8
File Format	PDF
ISBN	0780363752
DOI	10.1109/CEC.2000.870290
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-07-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Erbium Robot sensing systems Nervous system Computer networks Robotics and automation Artificial neural networks Automatic control Shape control Neural networks Stability
Content Type	Text
Resource Type	Article

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Evolutionary construction of behavior arbitration mechanisms based on dynamically-rearranging neural networks