This paper presents improvements to SOSDM based on ideas gleaned from the Danger Theory of immunology. In the new model, antibodies emit a signal describing their current level of contentment - monitoring the total level of contentment in the system provides a mechanism for determining when an immune response should occur, i.e. when new antibodies should be produced. It also provides a method of detecting catastrophic changes in the environment, i.e. significant changes in input data, and thus provides a means of removing antibodies. The new system, dSOSDM, is shown to be more robust and better able to deal with dynamically changing databases than SOSDM. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Hart, E., & Ross, P. (2003). Improving SOSDM: Inspirations from the Danger Theory. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2787, 194–203. https://doi.org/10.1007/978-3-540-45192-1_19
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