Artificial immune systems as a novel soft computing paradigm

Artificial immune systems (AIS) can be defined as computational systems inspired by theoretical immunology, observed immune functions, principles and mechanisms in order to solve problems. Their development and application domains follow those of soft computing paradigms such as artificial neural networks (ANN), evolutionary algorithms (EA) and fuzzy systems (FS). Despite some isolated efforts, the field of AIS still lacks an adequate framework for design, interpretation and application. This paper proposes one such framework, discusses the suitability of AIS as a novel soft computing paradigm and reviews those works from the literature that integrate AIS with other approaches, focusing ANN, EA and FS. Similarities and differences between AIS and each of the other approaches are outlined. New trends on how to create hybrids of these paradigms and what could be the benefits of this hybridization are also presented. Leandro N. de Castro would like to thank the Computing Laboratory and CNPq (Profix n. 540396/01-0) for the financial support and Prof. Dr. Fernando J. Von Zuben for his indispensable comments on the development of a framework for the AIS. Jon Timmis would like to thank the Computing Laboratory, UKC for their continued support in this new area of research.