Mapping artificial immune systems into learning classifier systems

This paper presents one form of mapping Artificial Immune Systems (AIS) into Learning Classifier Systems (LCS). Artificial Immune Systems can be defined as adaptive systems inspired by theoretical models and principles of the biological immune system and applied to solve problems in the most diverse domains, from biology to computing. Similar to Learning Classifier Systems, already used to model complex adaptive systems, a better understanding of Artificial Immune Systems can be obtained when they are analysed under the perspective of complex adaptive systems. One of the goals here is to determine complementary features of both systems (LCS and AIS), aiming at providing a novel mapping conception. The formal treatment proposed along the paper may then be used to integrate models for complex adaptive systems.