The complexity of the immune system is sometimes compared to that of the brain. Both systems can be viewed as composed of networks of elements; which endow them with interesting features for the development of computational tools with potentialities for problem solving. This paper has two main goals. First, to introduce the general features of immune networks to the artificial neural network (ANV) community. Second, it is an attempt to present a theoretical comparison between ANN and a standard neural network. The comparison is highly simplified and general, taking into account how each network is structured, their basic components and mechanisms of adaptation, and information processing capabilities.
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