Evolutionary algorithms have shown a great potential to develop the optimal neural networks that can change the architectures and learning rules according to the environments. In order to boost up the scalability and utilization, grammatical development has been considered as a promising encoding scheme of the network architecture in the evolutionary process. This paper presents a preliminary result to apply a grammatical development method called L-system to determine the structure of a modular neural network that was previously proposed by the authors. Simulation result with the recognition problem of handwrit- ten digits indicates that the evolved neural network has reproduced some of the characteristics of natural visual system, such as the organization of coarse and fine processing of stimuli in separate pathways.
|Title of host publication||Simulated Evolution and Learning - 2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998, Selected Papers|
|Editors||Bob McKay, Xin Yao, Charles S. Newton, Jong-Hwan Kim, Takeshi Furuhashi|
|Number of pages||8|
|ISBN (Print)||3540659072, 9783540659075|
|Publication status||Published - 1999|
|Event||2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998 - Canberra, Australia|
Duration: 1998 Nov 24 → 1998 Nov 27
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||2nd Asia-Pacific Conference on Simulated Evolution and Learning, SEAL 1998|
|Period||98/11/24 → 98/11/27|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 1999.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)