Conceptual Frameworks for Artificial Immune Systems

We propose that bio-inspired algorithms are best developed and analysed in the context of a multidisciplinary conceptual framework that provides for sophisticated biological models and well-founded analytical principles, and we outline such a framework here, in the context of Artificial Immune System (AIS) network models, and we discuss mathematical techniques for analysing the state dynamics of AIS. We further propose ways to unify several domains into a common meta-framework, in the context of AIS population models. We finally discuss a case study, and hint at the possibility of a novel instantiation of such a meta-framework, thereby allowing the building of a specific computational framework that is inspired by biology, but not restricted to any one particular biological domain.