Applying a New Multidimentional Framework to 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, agentoriented methodologies and related modeling techniques have become a priority for the development of large scale agentbased 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 remain an open field. The success of the agent paradigm requires systematic methodologies for the specification, analysis and design of “non toy” MAS applications. We here present a 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. The overall results of this comparative analysis are presented here. Results from this work have also lead us to propose a unification scheme, much in the same spirit as that of UML, for MAS methodologies. Our goal is to make MAS design and development more systematic and to contribute to the standardisation of MAS methodologies and platforms.