Abstract
This paper discusses three basic concepts: a) The behavioral management of artificial intelligence (At) namely the intelligent multi agent systems, b) a geometric property of an), object considered as an environment, and that define the average location of their weight and can completely describe the motion of any object "Uniform Mass, Common Shapes, Non-uniform Mass and a general shape" through space in terms of the translation of the center of gravity (g) of the object from one place to another and the rotation of the object about its center of gravity if it is free to rotate. c) Artificial immune system that imitates the biological theory called the immune system and the evolutionary computation called Discrimination-based Artificial Lymphocyte (that includes a Genetic Artificial Immune System GAIS): modeling the learning mechanism of Self and Non-self Discrimination for environment idiosyncrasy. The outcome of this research is an Artificial Immune System based Intelligent Multi Agent robotic that solves agent-based applications. This new and specific strategy is applied to a robot cooperation problem focusing on the center of gravity where autonomous mobile robots emulate natural behaviors of our cells and molecules and realize their group behaviors, and the results prove that our method has solved the problem successfully.