Genetic Algorithms and Evolutionary Computing (B-KUL-H02D1A)

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• M. J. S. John R. Koza Martin A. Keane, “Evolving inventions”, Scientific American, no. 288, pp. 52–59, 2003.
• Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs (3rd Ed.) London, UK, UK: Springer-Verlag, 1996, isbn: 3-540-60676-9.
• K. Sims, “Evolving 3d morphology and behavior by competition”, Artif. Life, vol. 1, no. 4, pp. 353–372, 1994, issn: 1064-5462.
• D. Floreano, L. Keller, and D. N. Deorum, Evolution of adaptive behaviour in robots by means of darwinian selection, 2010.
• C. Janikow, “A knowledge-intensive genetic algorithm for supervised learning”, English, Machine Learning, vol. 13, no. 2-3, pp. 189–228, 1993, issn: 0885-6125. doi: 10.1007/BF00993043.
• W. Spears and K. De Jong, “Using genetic algorithms for supervised concept learning”, in Tools for Artificial Intelligence, 1990.,Proceedings of the 2nd International IEEE Conference on, 1990, pp. 335–341. doi: 10. 1109/TAI.1990.130359.
• J. Grefenstette, “Optimization of control parameters for genetic algorithms”, Systems, Man and Cybernet- ics, IEEE Transactions on, vol. 16, no. 1, pp. 122–128, 1986, issn: 0018-9472. doi: 10.1109/TSMC.1986. 289288.
• B. McGinley, J. Maher, C. O’Riordan, and F. Morgan, “Maintaining healthy population diversity using adaptive crossover, mutation, and selection”, Evolutionary Computation, IEEE Transactions on, vol. 15, no. 5, pp. 692–714, 2011, issn: 1089-778X. doi: 10.1109/TEVC.2010.2046173.

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