ABSTRACT
Th e fi eld of immunological computation (IC) or artifi cial immune system (AIS) has been evolving steadily (Dasgupta, 1999; Forrest et al., 1994; Tarakanov and Dasgupta, 2000) since 1985. Th ere has been an increasing interest in the development of computational models inspired by several immunological principles (Perelson and Oster, 1979; Percus et al., 1993). Some models intend to mimic the abstract mechanisms in the biological immune system (BIS) to better understand its natural processes and simulate its dynamic behavior in the presence of antigens or pathogens; others, however, emphasize on designing artifacts-computational algorithms, techniques using simplifi ed concepts (sometime obsolete) of various immunological processes, and functionalities (Farmer et al., 1986; Hofmeyr and Forrest, 2000; De Castro and Von Zuben, 2000; Stepney et al., 2004). Table 3.1 summarizes the mostly studied computational models of BIS, whereas the details of these are described in Chapters 4 through 6. It shows the use of specifi c immunological concepts in diff erent models and their intended applications (discussed in Chapter 7).
