Abstract
According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on Genetic Network Programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.
| Original language | English |
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| Title of host publication | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 |
| Pages | 683-690 |
| Number of pages | 8 |
| Publication status | Published - 2004 Sep 13 |
| Event | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR, United States Duration: 2004 Jun 19 → 2004 Jun 23 |
Publication series
| Name | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 |
|---|---|
| Volume | 1 |
Conference
| Conference | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 |
|---|---|
| Country | United States |
| City | Portland, OR |
| Period | 04/6/19 → 04/6/23 |
ASJC Scopus subject areas
- Engineering(all)
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Cite this
Eto, S., Hirasawa, K., & Hu, J. (2004). Functional localization of genetic network programming and its application to a pursuit problem. In Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 (pp. 683-690). (Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004; Vol. 1).