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article · Expert Systems · 1998

Learning classifier system for graph coloring

Zoheir Ezziane

Cited by 0Open access

Abstract

In this paper, the use of genetic algorithms and classifiers systems in the graph coloring application was considered. A crossover derivative was developed to accommodate the graph coloring specifications. Also, a method for verifying and validating the new offspring coloring rules and regulations was considered. Through a series of experiments conducted on randomly generated graphs of a relatively small size, the importance of various parameters and their impact to the overall system performance is demonstrated and discussed. In conclusion, suggestions for future study regarding this topic are proposed and briefly discussed.

Cite this paper

APA 7

Ezziane, Z. (1998). Learning classifier system for graph coloring. Expert Systems, 15(4), 240–246. https://doi.org/10.1111/1468-0394.00081

MLA 9

Ezziane, Zoheir. “Learning classifier system for graph coloring.” Expert Systems, vol. 15, no. 4, 1998, pp. 240–46, https://doi.org/10.1111/1468-0394.00081.

Chicago

Ezziane, Zoheir. 1998. “Learning classifier system for graph coloring.” Expert Systems 15 (4): 240–46. https://doi.org/10.1111/1468-0394.00081.

Harvard

Ezziane, Z. (1998) ‘Learning classifier system for graph coloring’, Expert Systems, 15(4), pp. 240–246. Available at: https://doi.org/10.1111/1468-0394.00081.

BibTeX
@article{ezziane1998learning,
  title = {{Learning classifier system for graph coloring}},
  author = {Ezziane, Zoheir},
  journal = {Expert Systems},
  volume = {15},
  number = {4},
  pages = {240--246},
  year = {1998},
  doi = {10.1111/1468-0394.00081}
}

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