Geometrical insights into the dendritic cell algorithm

This work examines the dendritic cell algorithm (DCA) from a mathematical perspective. By representing the signal processing phase of the algorithm using the dot product it is shown that the signal processing element of the DCA is actually a collection of linear classifiers. It is further shown that the decision boundaries of these classifiers have the potentially serious drawback of being parallel, severely limiting the applications for which the existing algorithm can be potentially used on. These ideas are further explored using artificially generated data and a novel visualisation technique that allows an entire population of dendritic cells to be inspected as a single classifier. The paper concludes that the applicability of the DCA to more complex problems is highly limited. Categories and Subject Descriptors H.1 [Models and Principles]: [General]; I.6.4 [Simulation and Modeling]: Model Validation and Analysis General Terms Algorithms

• Type: Conference
• Year: 2009
• Where: GECCO
• Authors: Thomas Stibor, Robert Oates, Graham Kendall, Jonathan M. Garibaldi
• Keywords: Artificial Intelligence, Dendritic Cell Algorithm, Dendritic Cells, GECCO 2009, Signal Processing