| S. T. Wierzchon. Generating optimal repertoire of antibody strings in an artificial immune system. In M. A. Klopotek, M. Michalewicz, and S. T.Wierzchon, editors, Intelligent Information Systems, pages 119--133, Heidelberg New York, 2000. Pysical-Verlag. |
.... kind of negative selection , where detectors are screened against self and thus we generate a set of detectors that cover non self space [5] When implemented in artificial immune systems (AIS) a number of heuristic improvements can be made to the detector generation process (see for example [21]) One criticism that can be made of canonical negative selection is that it makes use of information from only one class (this, of course, is an advantage when no other feedback is available) However, when combined with clonal selection learning, the AIS can refine its classification ability. ....
S. T. Wierzchon. Generating optimal repertoire of antibody strings in an artificial immune system. In S. T. Wierzchon M. Klopotek, M. Michalewicz, editor, Intelligent Information Systems, Advances in Soft Computing, pages 119-133. Physica-Verlag/Springer Verlag, Heidelberg/New York, 2000.
No context found.
S. T. Wierzchon. Generating optimal repertoire of antibody strings in an artificial immune system. In M. A. Klopotek, M. Michalewicz, and S. T.Wierzchon, editors, Intelligent Information Systems, pages 119--133, Heidelberg New York, 2000. Pysical-Verlag.
No context found.
S. T. Wierzchon. Generating optimal repertoire of antibody strings in an artificial immune system. In Intelligent Information Systems, 119--133, 2000.
No context found.
S. T. Wierzchon. Generating optimal repertoire of antibody strings in an arti cial immune system. In Intelligent Information Systems, 119-133, 2000.
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