Coordination specification in multi-agent systems: from requirements to architecture with the Tropos methodology

ABSTRACT

The goal of this paper is to propose a new methodology for designing coordination between human agents and software agents and, ultimately, among software agents. The methodology is based on two key ideas. The first is that coordination should be designed in steps, according to a precise software engineering methodology, and starting from the specification of early requirements. The second is that coordination should be modeled as dependency between actors. Two actors may depend on one another because they want to achieve goals, acquire resources or execute a plan. The methodology used is based on Tropos, an agent oriented software engineering methodology presented in earlier papers. The methodology is presented with the help of a case study.

REFERENCES

• 1: R. A. Bourne, C. Excelente-Toledo, and N. R. Jennings. Run-time selection of coordination mechanisms in multi-agent systems. In Proc. of ECAI'2000, pages 348-352. IOS Press, 2000.
• 2: Craig Boutilier, Sequential Optimality and Coordination in Multiagent Systems, Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, p.478-485, July 31-August 06, 1999
• 3: C. Castelfranchi. Modeling Social Action for AI Agents. In IJCAI, pages 1567-1576, 1997.
• 4: E. H. Durfee. Practically Coordinating. AI Magazine, 20(1), 1999.
• 5: Clarence Ellis , Jacques Wainer, Groupware and computer supported cooperative work, Multiagent systems: a modern approach to distributed artificial intelligence, MIT Press, Cambridge, MA, 1999
• 6: S. Hayden, C. Carrick, and Q. Yang. Architectural design patterns for multi-agent coordination, 1999.
• 7: Michael N. Huhns , Larry M. Stephens, Multiagent systems and societies of agents, Multiagent systems: a modern approach to distributed artificial intelligence, MIT Press, Cambridge, MA, 1999
• 8: N. R. Jennings. Commitments and conventions: The foundation of coordination in multi-agent systems. The Knowledge Engineering Review, 8(3):223-250, 1993.
• 9: Thomas W. Malone , Kevin Crowston, The interdisciplinary study of coordination, ACM Computing Surveys (CSUR), v.26 n.1, p.87-119, March 1994 [doi>10.1145/174666.174668]
• 10: J. Mylopoulos and J. Castro. Tropos: A framework for requirements-driven software development. In J. Brinkkemper and A. Solvberg, editors, Information System Engineering: State of the Art and Research Themes, Lecture Notes in Computer Science. Springer-Verlag, 2000.
• 11: A. Newell. The knowledge level. Artificial Intelligence, 18:87-127, 1982.
• 12: J. Odell, H. Parunak, and B. Bauer. Extending UML for agents. In G. Wagner, Y. Lesperance, and E. Yu, editors, Proc. of the AOIS 2000 workshop at the 17th National conference on Artificial Intelligence, pages 3-17, Austin, TX, 2000.
• 13: A. Perini. A web advisor for integrated protection. In ECAI2000 WS AI in Agriculture and Nat.Res., 2000.
• 14: Paolo Bresciani , Anna Perini , Paolo Giorgini , Fausto Giunchiglia , John Mylopoulos, A knowledge level software engineering methodology for agent oriented programming, Proceedings of the fifth international conference on Autonomous agents, p.648-655, May 2001, Montreal, Quebec, Canada [doi>10.1145/375735.376477]
• 15: A. Perini, A. Susi, and F. Giunchiglia. Coordination specification in Multi-Agent Systems. from requirements to architecture with the Tropos methodology. Technical report, ITC-IRST, April 2002.
• 16: R. G. Smith. The contract net protocol: High-level communication and control in a distributed problem solver. In IEEE Transactions on Computers, volume C-29, pages 1104-1113, 1980.
• 17: Gerhard Weiss, Multiagent systems: a modern approach to distributed artificial intelligence, MIT Press, Cambridge, MA, 1999