Agent-Based Modeling and Simulation of Artificial Immune Systems

Abstract

Agent-based modeling and simulation is a way to model the behavior of populations of components and their interactions within a system. The key of this approach is to model the components of the system as autonomous agents and to simulate their behavior for evaluating the system as a whole. That is very useful for observing the emergence of properties in social, biological, environmental or financial systems, among others. Artificial immune systems, which is a sub field of artificial intelligence, comprises systems modeled by simplifying models from the biological immune system. If agent-based modeling and simulation is used as a laboratory for understanding the biological immune system then, it can also be used for transferring the observed principles into artificial immune system models or for evaluating models that have been already adapted for solving technical problems. This paper presents first, a methodology for transferring principles of the biological immune system into the field of artificial immune systems. Then, it presents a brief explanation of the behavior of the cells of the biological immune system, which are treated as internal agents inside a biological organism. Afterwards, the modeling of some selected type of cells and the simulation of the whole simplified system are presented. In the end, the principles of that simplified system are transferred into the design of an alarm management system for the smart grid.