Patterns d'Analyse pour l'Ingénierie de Systèmes d'Information à base d'Agents : Une Application au Domaine du Transport

National audienceIntelligent Transport Information Systems may find benefit of using agent-based solutions. Actually, transport information systems require adaptability to varying changes in offers, and unexpected occurring events. Agents and multiagent systems provide such requirements. Unfortunately, agent-based information systems such as other distributed, asynchronous, loose-coupling applications are difficult to design and implement due to lack of best practices to ease development. This paper describes an approach based on software pattern reuse facilitating engineering of such systems. Patterns are generic solutions to frequently occurring problems. Metamodel represents and structures agent concepts. Fourteen analysis patterns have been specified from this metamodel and describe conceptual entities for the design of an agent-based IS application. Reuse support patterns help designers to reuse former patterns during the information system application engineering

Towards a More Expressive and Refinable Multiagent System Engineering Methodology Shiva Vafadar

In this paper, we improve and extend the MaSE methodology to bridge the gaps in this methodology. First, we propose an improvement process and, based on this process, we report the discovered gaps and weaknesses in the methodology during different phases of case study life cycle. For removing the reported weaknesses, we introduce a "Role Schema " to document roles properties and the "Knowledge Modeling " step in order to model knowledge of each single agent in the analysis phase of methodology. We also propose an "Agent–Object model " to decrease design and implementation complexity and improve efficiency of the developed agent-based system. For evaluating the proposed refinements and extensions we have analyzed and designed the CASBA multiagent system with the improved MaSE. We will show that these improvements will increase expressiveness and refinability of the methodology and maintainability of the developed agent-based system