Artificial Immune Systems

The Biological immune system is a highly parallel, distributed, and adaptive system. It uses learning, memory, and associative retrieval to solve recognition and classification tasks. In particular, it learns to recognize relevant patterns, remember patterns that have been seen previously, and use combinatorics to construct pattern detectors efficiently. These remarkable information processing abilities of the immune system provide important aspects in the field of computation. This emerging field is sometimes referred to as Immunological Computation, Immunocomputing, or Artificial Immune Systems (AIS). Although it is still relatively new, AIS, having a strong relationship with other biology-inspired computing models, and computational biology, is establishing its uniqueness and effectiveness through the zealous efforts of researchers around the world.

Books on Artificial Immune Systems:

• "Immunological Computation: Theory and Applications" (Cover Page).
  
• "Artificial Immune Systems and Their Applications"
• Dr. Dipankar Dasgupta's talk on Artificial Immune Systems at the University of Illinois at Urbana Champaign (NIGEL 2006 workshop).