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A Multi-Agent System for Emergent Process Management

  • John Debenham
Conference paper

Abstract

A multi-agent system manages emergent business processes. The agents in this system all have the same generic architecture. The generic agent architecture is a three-layer BDI, hybrid, multi-agent architecture. The architecture copes with plans whose goals develop and mutate. The agents in the system choose their course of action on the basis of estimates of the likelihood of a choice leading to success, and on estimates of the time, cost and value of making a choice.

Keywords

Business Process Success Condition Process Instance Agent Architecture Emergent Process 
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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References

  1. 1.
    Norman, TJ, Jennings, NR, Faratin, P and Mamdani, EH. Designing and Implementing a Multi-Agent Architecture for Business Process Management. In J.P Müller, M.J. Wooldridge & N.R. Jennings (Eds). Intelligent Agents III. Springer-Verlag, 1997.Google Scholar
  2. 2.
    Jennings, NR and Wooldridge, MJ (eds). Agent Technology: Foundations, Applications and Markets. Springer-Verlag: Berlin, Germany, 1998.Google Scholar
  3. 3.
    Huhns, MH and Singh, MP. Managing heterogeneous transaction workflows with cooperating agents. In N.R. Jennings and M. Wooldridge, (eds). Agent Technology: Foundations, Applications and Markets. Springer-Verlag: Berlin, Germany, pp. 219239, 1998.Google Scholar
  4. 4.
    Debenham, JK. A Single-Agent Architecture Supports Decision Making. In Proceedings Eighteenth International Conference on Knowledge Based Systems and Applied Artificial Intelligence, ES’98: Applications and Innovations in Expert Systems VI. Cambridge UK, December 1998, pp 85–98.Google Scholar
  5. 5.
    Debenham, JK. An Experimental Agent-based Workflow System. In proceedings Third International Conference on The Practical Application of Intelligent Agents and Multi-Agents PAAM’98, London, March 1998, pp 101–110.Google Scholar
  6. 6.
    Weiss, G. Multi-Agent Systems. The MIT Press, Cambridge, MA, 1999.Google Scholar
  7. 7.
    Jennings, NR, Sycara, K and Wooldridge, MJ. A Roadmap of Agent Research and Development. Autonomous Agents and Multi-Agent Systems, 1, 7–38. Kluwer Academic Publishers, 1998.CrossRefGoogle Scholar
  8. 8.
    Müller, JP. The Design of Intelligent Agents: A Layered Approach(Lecture Notes in Computer Science, 1177 ). Springer Verlag, May 1997.Google Scholar
  9. 9.
    Rao, AS and Georgeff, MP. BDI Agents: From Theory to Practice. In Proceedings 1st Int Conf on Multi-Agent Systems (ICMAS-95), San Francisco, USA, pp 312–319, June 1995.Google Scholar
  10. 10.
    Finin, Labrou, TY and Mayfield, J. KQML as an agent communication language. In Jeff Bradshaw (Ed.) Software Agents. MIT Press, 1997.Google Scholar
  11. 11.
    Zukunft, O. and Rump, F. From Business Process Modelling to Workflow Management: An Integrated Approach. In B. Scholz-Reiter and E. Stickel (Eds) Business Process Modelling. Springer-Verlag, 1996.Google Scholar
  12. 12.
    . Sutton, RS and Barto, AG. Reinforcement Learning. MIT Press, 1998.Google Scholar
  13. 13.
    Wellman, MP and Derthick, M. Formulation of Tradeoffs in Planning Under Uncertainty. Morgan Kaufman Publishers, 1990.Google Scholar

Copyright information

© Springer-Verlag London 2000

Authors and Affiliations

  • John Debenham
    • 1
  1. 1.Computing SciencesUniversity of TechnologySydneyAustralia

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