A simple artificial immune system (SAIS) for generating classifier systems

Current artificial immune system (AIS) classifiers have two major problems: (1) their populations of B-cells can grow to huge proportions and (2) optimizing one B-cell (part of the classifier) at a time does not necessarily guarantee that the B-cell pool (the whole classifier) will be optimized. In this paper, we describe the design of a new AIS algorithm and classifier system called simple AIS (SAIS). It is different from traditional AIS classifiers in that it takes only one B-cell, instead of a B-cell pool, to represent the classifier. This approach ensures global optimization of the whole system and in addition no population control mechanism is needed. We have tested our classifier on four benchmark datasets using different classification techniques and found it to be very competitive when compared to other classifiers