Abstract
The authors examine aspects of machine learning by classifier systems that use genetic algorithms. In particular, adaptive image learning and classification are considered. Standard classifier systems are not well suited for seeking out multiple goals as is necessary in image learning and classification problems. To improve the performance of standard classifier systems for the image learning task, several modifications are suggested. The modifications result in a far better performance for classifier system on the ImageLearn domain.
Original language | English (US) |
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Title of host publication | IEEE Proceedings of the National Aerospace and Electronics Conference |
Editors | Anon |
Publisher | IEEE Computer Society |
Pages | 705-710 |
Number of pages | 6 |
Volume | 2 |
State | Published - 1989 |
Externally published | Yes |
Event | Proceedings of the IEEE 1989 National Aerospace and Electronics Conference - NAECON 1989 - Dayton, OH, USA Duration: May 22 1989 → May 26 1989 |
Other
Other | Proceedings of the IEEE 1989 National Aerospace and Electronics Conference - NAECON 1989 |
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City | Dayton, OH, USA |
Period | 5/22/89 → 5/26/89 |
ASJC Scopus subject areas
- General Engineering