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 |
|---|---|
| Title of host publication | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 |
| Pages | 683-690 |
| Number of pages | 8 |
| Volume | 1 |
| Publication status | Published - 2004 |
| Event | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 - Portland, OR Duration: 2004 Jun 19 → 2004 Jun 23 |
Other
| Other | Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004 |
|---|---|
| City | Portland, OR |
| Period | 04/6/19 → 04/6/23 |
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ASJC Scopus subject areas
- Engineering(all)
Cite this
Functional localization of genetic network programming and its application to a pursuit problem. / Eto, Shinji; Hirasawa, Kotaro; Furuzuki, Takayuki.
Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004. Vol. 1 2004. p. 683-690.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Functional localization of genetic network programming and its application to a pursuit problem
AU - Eto, Shinji
AU - Hirasawa, Kotaro
AU - Furuzuki, Takayuki
PY - 2004
Y1 - 2004
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=4344684781&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=4344684781&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:4344684781
SN - 0780385152
SN - 9780780385153
VL - 1
SP - 683
EP - 690
BT - Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004
ER -