Implicit cooperation and Antagonism in Multi-Agent Systems

This paper fits in the framework of Distributed Artificial Intelligence andmore specifically in the field of Multi-Agent Systems (MAS). We show why antagonism should be considered in MAS made up of autonomous agents and how these systems can even turn antagonism to advantage. We present a case study of a MAS aimed at exploring the possibilities of antagonism, oriented towards mobile robotics applications. Experimental results relative to a preliminary study of antagonism, namely implicit cooperation, illustrating the complexity and the power of this approach, are reported.