TOWARDS A KERNELBASED MODEL FOR ARTIFICIAL IMMUNE NETWORKS

This paper presents an adaptation to the strategy of kernel methods of a wellkn own artificial immune network. This adaptation brings to artificial immune systems, for the first time, some of the advantages of kernel methods, such as the ability to deal with non-vector data and the mapping to high-dimensional spaces through the kernel trick. Preliminar y experiments were carried out in order to get some insights of the behavior of the proposed model.