Transaction Agent Modelling: From Experts to Concepts to Multi-Agent Systems

  • Richard Hill
  • Simon Polovina
  • Dharmendra Shadija
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4068)


Whilst the Multi-Agent System (MAS) paradigm has the potential to enable complex heterogeneous information systems to be integrated, there is a need to represent and specify the nature of qualitative conceptual transactions in order that they are adequately comprehended by a goal-directed MAS. Using the Transaction Agent Model (TrAM) approach we examine the use of Conceptual Graphs to model an extension to an existing MAS in the community healthcare domain, whereby the existing agent capabilities are augmented with a robust set of behaviours that provide emergency healthcare management. We illustrate how TrAM serves to enrichen the requirements gathering process, whilst also supporting the definition and realisation of quantitative measures for the management of qualitative transactions.


Transaction Model Conceptual Graph Qualitative Concept Broker Agent Complex Information System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Bauer, B., Muller, J.P., Odell, J.: Agent UML: A Formalism for Specifying Multi-agent Software Systems. In: Ciancarini, P., Wooldridge, M.J. (eds.) Agent-Oriented Software Engineering, vol. 1957, pp. 91–104. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  2. 2.
    Beer, M.D., Bench-Capon, T.J.M., Sixsmith, A.: Some Issues in Managing Dialogues between Information Agents. In: Bench-Capon, T.J.M., Soda, G., Tjoa, A.M. (eds.) DEXA 1999. LNCS, vol. 1677, pp. 521–530. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  3. 3.
    Beer, M.D., Huang, W., Sixsmith, A.: Using Agents to Build a Practical Implementation of the InCA (Intelligent Community Alarm) System. In: Jain, L.C., Chen, Z., Ichalkaranje, N. (eds.) Intelligent Agents & their Applications, pp. 320–345. Springer, Heidelberg (2002)Google Scholar
  4. 4.
    Bresciani, P., Giorgini, P., Giunchiglia, F., Mylopoulos, J., Perini, A.: TROPOS: An Agent-Oriented Software Development Methodology. Journal of Autonomous Agents and Multi-Agent Systems 8, 203–236 (2004)CrossRefGoogle Scholar
  5. 5.
    Dau, F.: The Logic System of Concept Graphs with Negation: And Its Relationship to Predicate Logic. LNCS, vol. 2892. Springer, Heidelberg (2003)zbMATHCrossRefGoogle Scholar
  6. 6.
    DeLoach, S.: Multi-Agent Systems Engineering: A Methodology and Language for Designing Agent Systems (1999),
  7. 7.
    Foundation For Intelligent Physical Agents, Fipa Iterated Contract Net Interaction Protocol Specification. (Accessed 2005) (November 21, 2000),
  8. 8.
    Fuxman, A., Kazhamiakin, R., Pistore, M., Roveri, M.: Formal Tropos: language and semantics (Version 1.0) (Accessed: 2005) (November 4, 2003),
  9. 9.
    Geerts, G., McCarthy, W.: Database Accounting Systems. In: Williams, B., Sproul, B.J. (eds.) Information Technology Perspectives in Accounting: and Integrated Approach, pp. 159–183. Chapman and Hall Publishers, Boca Raton (1991)Google Scholar
  10. 10.
    Georgeff, M.P., Pell, B., Pollack, M.E., Tambe, M., Wooldridge, M.: The Belief-Desire-Intention Model of Agency. In: Rao, A.S., Singh, M.P., Müller, J.P. (eds.) ATAL 1998. LNCS (LNAI), vol. 1555, pp. 1–10. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  11. 11.
    Hill, R., Polovina, S., Beer, M.D.: From Concepts to Agents: Towards a Framework for Multi-Agent System Modelling. In: Hill, R., Polovina, S., Beer, M.D. (eds.) Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2005, Utrecht University, Netherlands, July 25-29, pp. 25–29. ACM Press, New York (2005)Google Scholar
  12. 12.
    Hill, R., Polovina, S., Beer, M.D.: Improving AOSE with an Enriched Modelling Framework. In: 6th International Workshop on Agent Oriented Software Engineering (AOSE 2005), Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2005, Utrecht University, Netherlands, July 25. ACM Press, New York (in press, 2005)Google Scholar
  13. 13.
    Hill, R., Polovina, S., Beer, M.D.: Managing Community Healthcare Information in a Multi-Agent System Environment. In: First International Workshop on Multi-Agent Systems for Medicine, Computational Biology, and Bioinformatics (BIOMED), Fourth International Joint Conference on Autonomous Agents and Multi-Agent Systems, AAMAS 2005, Utrecht University, Netherlands, July 25, ACM Press, New York (in press, 2005)Google Scholar
  14. 14.
    Hill, R., Polovina, S., Beer, M.D.: Towards a Deployment Framework for Agent-Managed Community Healthcare Transactions. In: The Second Workshop on Agents Applied in Health Care. Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), Augest 23-24, 2004, pp. 13–21. IOS Press, Valencia (2004)Google Scholar
  15. 15.
    Holzman, T.G.: Computer-human interface solutions for emergency medical care. Interactions 6(3), 13–24 (1999)CrossRefGoogle Scholar
  16. 16.
    Nwana, H., Ndumu, D., Lee, L., Collis, J.: ZEUS: A Tool-Kit for Building Distributed Multi-Agent Systems. Applied Artifical Intelligence Journal 13(1), 129–186 (1999)CrossRefGoogle Scholar
  17. 17.
    Padgham, L., Winikoff, M.: Prometheus: A Methodology for Developing Intelligent Agents. In: Proceedings of the Third International Workshop on Agent-Oriented Software Engineering, at AAMAS 2002 (2002)Google Scholar
  18. 18.
    Polovina, S.: The Suitability of Conceptual Graphs in Strategic Management Accountancy (PhD Thesis) (1993), available at:
  19. 19.
    Polovina, S., Hill, R., Crowther, P., Beer, M.D.: Multi-Agent Community Design in the Real, Transactional World: A Community Care Exemplar. In: Pfeiffer, H., Wolff, K.E., Delugach, H.S. (eds.) Conceptual Structures at Work: Contributions to ICCS 2004 (12th International Conference on Conceptual Structures), pp. 69–82. Shaker Verlag, Aachen (2004)Google Scholar
  20. 20.
    Polovina, S., Hill, R.: Enhancing the Initial Requirements Capture of Multi-Agent Systems through Conceptual Graphs. In: Dau, F., Mugnier, M.-L., Stumme, G. (eds.) ICCS 2005. LNCS, vol. 3596, pp. 439–452. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  21. 21.
    Sowa, J.F.: Conceptual Structures: Information Processing in Mind and Machine. Addison-Wesley, Reading (1984)zbMATHGoogle Scholar
  22. 22.
    OMG: Unified Modeling Language Resource Page (2004),
  23. 23.
    Wooldridge, M., Jennings, N., Kinny, D.: The Gaia Methodology for Agent-Oriented Analysis and Design. In: Autonomous Agents and Multi-Agent Systems, vol. 3, pp. 285–312 (2000)Google Scholar
  24. 24.
    Zambonelli, F., Jennings, N.R., Wooldridge, M.: ‘Developing multiagent systems: The Gaia methodology. ACM Trans.Softw.Eng.Methodol. 12, 317–370 (2003)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Richard Hill
    • 1
  • Simon Polovina
    • 1
  • Dharmendra Shadija
    • 1
  1. 1.Web and Multi-Agent Research GroupSheffield Hallam UniversitySheffieldUK

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