Immune system (IS) simulations have several applications. such as biological theory testing or as a complement in the development of improved drugs. This paper presents an agent based approach to simulate the IS response to bacterial infection challenge. The agent simulator is implemented in a discrete time and two- dimensional space, and composed by two layers: A) a specialized cellular automata responsible for substance diffusion and reactions; and b) the layer where agents move, act and interact. The IS model focuses upon low level cellular receptor interactions, receptor diversity and genetic-ruled agents, aiming to observe and study the resultant emergent behavior. The model reproduces the following IS behavioral characteristics: specificity and specialization, immune memory and vaccine immunization. © 2008 EUROSIS-ETI.