Abstract
Recently many studies have been made on automatic design of the complex systems by using the evolutionary optimization techniques such as Genetic Algorithms (GA), Evolution Strategy (ES), Evolutionary Programming (EP) and Genetic Programming (GP). It is generally recognized that these techniques are very useful for optimizing fairly complex systems such as generation of intelligent behavior sequences of robots. In this paper, a new method named Genetic network Programming (GNP) is proposed in order to acquire these behavior sequences efficiently. GNP is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure. Agents behave according to the contents of the nodes and their connections in GNP. In order to obtain better structure, GNP changes itself by using evolutionary optimization techniques.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Publisher | IEEE |
| Pages | 3829-3834 |
| Number of pages | 6 |
| Volume | 5 |
| Publication status | Published - 2000 |
| Externally published | Yes |
| Event | 2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA Duration: 2000 Oct 8 → 2000 Oct 11 |
Other
| Other | 2000 IEEE International Conference on Systems, Man and Cybernetics |
|---|---|
| City | Nashville, TN, USA |
| Period | 00/10/8 → 00/10/11 |
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ASJC Scopus subject areas
- Hardware and Architecture
- Control and Systems Engineering
Cite this
Genetic network programming - application to intelligent agents. / Katagiri, H.; Hirasawa, K.; Furuzuki, Takayuki.
Proceedings of the IEEE International Conference on Systems, Man and Cybernetics. Vol. 5 IEEE, 2000. p. 3829-3834.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Genetic network programming - application to intelligent agents
AU - Katagiri, H.
AU - Hirasawa, K.
AU - Furuzuki, Takayuki
PY - 2000
Y1 - 2000
N2 - Recently many studies have been made on automatic design of the complex systems by using the evolutionary optimization techniques such as Genetic Algorithms (GA), Evolution Strategy (ES), Evolutionary Programming (EP) and Genetic Programming (GP). It is generally recognized that these techniques are very useful for optimizing fairly complex systems such as generation of intelligent behavior sequences of robots. In this paper, a new method named Genetic network Programming (GNP) is proposed in order to acquire these behavior sequences efficiently. GNP is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure. Agents behave according to the contents of the nodes and their connections in GNP. In order to obtain better structure, GNP changes itself by using evolutionary optimization techniques.
AB - Recently many studies have been made on automatic design of the complex systems by using the evolutionary optimization techniques such as Genetic Algorithms (GA), Evolution Strategy (ES), Evolutionary Programming (EP) and Genetic Programming (GP). It is generally recognized that these techniques are very useful for optimizing fairly complex systems such as generation of intelligent behavior sequences of robots. In this paper, a new method named Genetic network Programming (GNP) is proposed in order to acquire these behavior sequences efficiently. GNP is composed of plural nodes for agents to execute simple judgment/processing and they are connected with each other to form a network structure. Agents behave according to the contents of the nodes and their connections in GNP. In order to obtain better structure, GNP changes itself by using evolutionary optimization techniques.
UR - http://www.scopus.com/inward/record.url?scp=0034516030&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0034516030&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:0034516030
VL - 5
SP - 3829
EP - 3834
BT - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
PB - IEEE
ER -