Abstract
The dendritic cell algorithm is an immune-inspired technique for processing time-dependant data. Here we propose it as a possible solution for a robotic classification problem. The dendritic cell algorithm is implemented on a real robot and an investigation is performed into the effects of varying the migration threshold median for the cell population. The algorithm performs well on a classification task with very little tuning. Ways of extending the implementation to allow it to be used as a classifier within the field of robotic security are suggested.
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Oates, R., Greensmith, J., Aickelin, U., Garibaldi, J., Kendall, G. (2007). The Application of a Dendritic Cell Algorithm to a Robotic Classifier. In: de Castro, L.N., Von Zuben, F.J., Knidel, H. (eds) Artificial Immune Systems. ICARIS 2007. Lecture Notes in Computer Science, vol 4628. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73922-7_18
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DOI: https://doi.org/10.1007/978-3-540-73922-7_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73921-0
Online ISBN: 978-3-540-73922-7
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