In this report the immune system and its adaptive properties are described and a simple artificial immune system (AIS) model based on the clonal selection theory is presented. This immune system model is demonstrated to be capable of learning the structure of novel antigens, of memory for previously encountered antigens, and of being able to use its memory to respond more efficiently to antigens related to ones it has previously seen (cross-reactivity). The learning, memory and cross-reactivity of the AIS are fruitfully applied to the problem of fuzzy resource identification. Interesting antigen/antibody relationships are also identified.
|Title of host publication||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Number of pages||5|
|Publication status||Published - 2001|
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)