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Immunology as a Metaphor for Computational ... - Napier University

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Bibliography 212[Smith and Coit, 1997] Smith, A. and Coit, D. (1997). Handbook of EvolutionaryComputing, chapter Constraint Handling Techniques - Penalty Functions. Ox<strong>for</strong>d<strong>University</strong> Press. Chapter C5.2.[Smith et al., 1996] Smith, D., Forrest, S., and Perelson, A. (1996). Immunologicalmemory is <strong>as</strong>sociative. In Workshop Notes, Workshop 4: Immunity B<strong>as</strong>ed Systems,International Conference on Multiagent Systems, pages 62–70. Kyoto, Japan.[Smith et al., 1999] Smith, D., Forrest, S., and Perelson, A. (1999). Artificial ImmuneSystems and Their Applications, chapter Immunological Memory is Associative,pages 105–112. Springer-Verlag.[Smith et al., 1993] Smith, R., Forrest, S., and Perelson, A. (1993). Searching <strong>for</strong> diverse,cooperative populations with genetic algorithms. Evolutionary Computation,1(2):127–149.[Stadnyk, 1987] Stadnyk, I. (1987). Schema recombination in pattern recognitionproblems. In who, editor, Proceedings of the 2nd International Conference on GeneticAlgorithms and their Applications, page ?, Hillside, NJ. Lawrence ErlbaumAssoc.[Tew and Mandel, 1979] Tew, J. and Mandel, T. (1979). Prolonged antigen half-lifein the lymphoid follicules of antigen-specifically immunized mice. <strong>Immunology</strong>,37:69–76.[Timmis, 2000a] Timmis, J. (2000a). On parameter adjustment of the immune inspiredmachine learning algorithm AINE. Technical Report 12-00, Computing Laboratory,Univeristy of Kent at Canterbury, Canterbury, Kent. CT2 7NF.[Timmis, 2000b] Timmis, J. (2000b). Visualising artificial immune networks. TechnicalReport UWA-DCS-00-034, <strong>University</strong> of Wales, Aberystwyth.[Timmis and Neal, 2001] Timmis, J. and Neal, M. (2001). A resource limited artificialimmune system <strong>for</strong> data analysis. Knowledge B<strong>as</strong>ed Systems, 14(3-4):121–130.

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