Description
Book SynopsisClearly, nature has been very effective in creating organisms that are capable of protecting themselves against a wide variety of pathogens such as bacteria, fungi, and parasites. The powerful information-processing capabilities of the immune system, such as feature extraction, pattern recognition, learning, memory, and its distributive nature provide rich metaphors that researchers are finding very useful for the development of computational models. While some of these models are designed to give us a better understanding of the immune system, other models are being developed to solve complex real-world problems such as anomaly detection, pattern recognition, data analysis (clustering), function optimization, and computer security.
Immunological Computation: Theory and Applications is devoted to discussing different immunological mechanisms and their relation to information processing and problem solving. This unique volum
Table of Contents
Immunology Basics. Modeling the Biological Immune System. Negative Selection. Artificial Immune Networks. Clonal Selection Algorithm and Hybrid Models. Applications.
