Generalization in the XCS Classifier System
@inproceedings{Wilson1998GeneralizationIT, title={Generalization in the XCS Classifier System}, author={S. Wilson}, year={1998} }
10 Generalization in the XCS Classifier System evaluation involved testing the program on all 64 inputs from the 6-multiplexer domain, so that the total number of inputs was 15,680,000. This differs by a factor of 7,840 from the total number required by XCS. Thus, conservatively, the amounts of " experience " required by XCS and GP to learn the 6-multiplexer differ by three orders of magnitude. There is not space to explore the reasons behind the difference. Instead, and in GP's favor, we note… CONTINUE READING
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References
SHOWING 1-10 OF 12 REFERENCES
XCS Classifier System Reliably Evolves Accurate, Complete, and Minimal Representations for Boolean Functions
- Mathematics
- 1998
- 152
- PDF
Classifier Fitness Based on Accuracy
- Mathematics, Computer Science
- Evolutionary Computation
- 1995
- 1,434
- PDF
Co-Evolving Co-Operative Populations of Rules in Learning Control Systems
- Computer Science
- Evolutionary Computing, AISB Workshop
- 1994
- 20
Learning by statistical cooperation of self-interested neuron-like computing elements.
- Computer Science, Medicine
- Human neurobiology
- 1985
- 210