A Multidimentional Framework for the Evaluation of Multiagent System Methodologies

Because of the great interest in using multiagent systems (MAS) in a wide variety of applications in recent years, agent-oriented methodologies and related modeling techniques have become a priority for the development of large scale agent-based systems. The work we present here belongs to the disciplines of Software Engineering and Distributed Artificial Intelligence. More specifically, we are interested in software engineering aspects involved in the development of multiagent systems (MAS). Several methodologies have been proposed for the development of MAS. For the most part, these methodologies remain incomplete: they are either an extension of object-oriented methodologies or an extension of knowledge-based methodologies. In addition, too little effort has gone into the standardization of MAS methodologies, platforms and environments. It seems obvious, therefore, that software engineering aspects of the development of MAS still remains an open field. The success of the agent paradigm requires systematic methodologies for the specification, analysis and design of “non toy” MAS applications. We present in this paper a new framework called MUCCMAS, which stands for MUltidimensional framework of Criteria for the Comparison of MAS methodologies, that enabled us to make a comparative analysis of existing main MAS methodologies.