Designing Artificial Immune System Based on Clonal Selection: Using Agent-Based Modeling Approach

Bio-inspired computing is the idea to emulate and to get inspirations from biological systems which is then used to solve complex problems. Artificial immune systems, as one of the bio-inspired computing has contributed in solving complex problems. From one generation to another generation, AIS´s practitioners realize that to get better algorithms we need the inspiration with the better understanding about the behavior of the immune system. Modeling is the key to get better understanding and inspiration from immune system. Agent-based modeling can be used because of the components of the immune system can be described as agents that interact with each other and set up a system behavior. There are two approaches to agent-based modeling, i.e. modeling of the immune system itself and model the artificial immune system. In this paper we design a model for immune system using agent-based approach. This model specifically based on clonal selection and its behavior. The design of model are using UML diagram to describe the behavior and the interaction of agents. This design can be used for simulating existing artificial immune system models, developing new artificial immune system models, or evaluating artificial immune system models that have been already adapted to technical problems.