Proceedings of the KIEE Conference (대한전기학회:학술대회논문집)

The Korean Institute of Electrical Engineers (대한전기학회)
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Strategies for Evolution in Neural Networks based on Cellular Automata

셀룰라 오토마타 기반 신경 회로망의 진화를 위한 전략

  • Jo, Yong-Goon (School of Electrical & Electronic Engineering Chung-Ang Univ.) ;
  • Lee, Won-Hee (School of Electrical & Electronic Engineering Chung-Ang Univ.) ;
  • Kang, Hoon (School of Electrical & Electronic Engineering Chung-Ang Univ.)
  • 조용군 (중앙대학교 공과대학 전자전기공학부) ;
  • 이원희 (중앙대학교 공과대학 전자전기공학부) ;
  • 강훈 (중앙대학교 공과대학 전자전기공학부)
  • Published : 1998.07.20
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Abstract

Cellular automata are dynamical systems in which space and time are discrete, where each cell has a finite number of states and updates its states by interactive rules among the cell-neighborhood. From the characteristics of self-reproduction and self- organization, it is possible to create a neural network which has the specific patterns or structures dynamically. CAM-Brain is a kind of such neural network system which evolves its structure by adopting evolutionary computations like genetic algorithms (GA). In this paper, we suggest the evolution strategies for the structure of neural networks based on cellular automata.

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