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 |
|---|---|
| Pages (from-to) | 3829-3834 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE International Conference on Systems, Man and Cybernetics |
| Volume | 5 |
| Publication status | Published - 2000 Dec 1 |
| Externally published | Yes |
| Event | 2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA Duration: 2000 Oct 8 → 2000 Oct 11 |
ASJC Scopus subject areas
- Control and Systems Engineering
- Hardware and Architecture