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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.7 No.3
- 발행연도
- 2007.9
- 수록면
- 176 - 181 (6page)
이용수
초록· 키워드
오류제보하기
This paper presents evolvable neural networks based on a developmental model for navigation control of autonomous mobile robots in dynamic operating environments. Bio-inspired mechanisms have been applied to autonomous design of artificial neural networks for solving practical problems. The proposed neural network architecture is grown from an initial developmental model by a set of production rules of the L-system that are represented by the DNA coding. The L-system is based on parallel rewriting mechanism motivated by the growth models of plants. DNA coding gives an effective method of expressing general production rules. Experiments show that the evolvable neural network designed by the production rules of the L-system develops into a controller for mobile robot navigation to avoid collisions with the obstacles.
목차
Abstract
1. Introduction
2. Evolvable Neural Network Representation
3. Design of Evolvable Neural Networks Based on Developmental Models
4. Experiment Results
5. Conclusion
References
참고문헌 (19)
참고문헌 신청
X. Yao , 1999 , Evolving artificial neural networks 87 (9) : 1423 ~ 1447
S. W. Moon , March2001 , Block-based Neural Netwo 12 (2) : 307 ~ 317
M. Y. Nam , 2004 , A Novel Image Preprocessing by Evolvable Neural Network 3215 : 843 ~ 854
P. J. Angeline , 199 , ″An evolutionary algorithm that constructs recurrent neural networks ″ IEEE Trans. on Neural Networks 5 : 54 ~ 65
X. Yao , 1994. , ″A new evolutionary system for evolving artificial neural networks ″ IEEE Trans. on Neural Networks 8 : 54 ~ 65
S. W. Moon , March2001 , Block-based Neural Netwo 12 (2) : 307 ~ 317
M. Y. Nam , 2004 , A Novel Image Preprocessing by Evolvable Neural Network 3215 : 843 ~ 854
P. J. Angeline , 199 , ″An evolutionary algorithm that constructs recurrent neural networks ″ IEEE Trans. on Neural Networks 5 : 54 ~ 65
X. Yao , 1994. , ″A new evolutionary system for evolving artificial neural networks ″ IEEE Trans. on Neural Networks 8 : 54 ~ 65
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UCI(KEPA) : I410-ECN-0101-2009-028-014915649