Robustness Reducing Model of Distributed Artificial Immune System

With the model of reducing robustness for the distributed multi-agent system, the robustness analysis problem of the distributed artificial immune system (DAIS) was reduced into robustness analysis problems of all the independent modules of the system. The artificial immune system (AIS) included the module of modeling the normal model, the module of detecting selfs and non-selfs, the module of recognizing known non-selfs, the module of learning unknown non-selfs, the module of eliminating non-selfs and the module of repairing the damaged system. After analyzing the robustness of the artificial immune system with the problem reduction method, the model of reducing robustness of the distributed artificial immune system was built. Proved by some theorems, the model of reducing robustness can reduce and simplify the robustness analysis problem of the distributed artificial immune system, and the problem can be solved after the robustness analysis problems of all the modules are solved. Therefore, the model of reducing robustness of the distributed artificial immune system is a useful tool to analyze robustness, and provides an effective approach for analyzing robustness of complex artificial immune system.