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Flexible and Emergent Workflows Using Adaptive Agents

  • Arcady Rantrua
  • Marie-Pierre Gleizes
  • Chihab Hanachi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8083)

Abstract

Most of existing workflow systems are rigid since they require to completely specify processes before their enactment and they also lack flexibility during their execution. This work proposes to view a workflow as a set of cooperative and adaptive agents interleaving its design and its execution leading to an emergent workflow. We use the theory of Adaptive Multi-Agent Systems (AMAS) to provide agents with adaptive capabilities and the whole multi-agent system with emergent “feature”. We provide a meta-model linking workflow and AMAS concepts, and the specification of agent behavior and the resulting collaborations. A simulator has been implemented with the Make Agent Yourself platform.

Keywords

workflow multi-agent system flexibility adaptation emergence 

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References

  1. 1.
    Ermolayev, V., Jentzsch, E., Karsayev, O., Keberle, N., Matzke, W.-E., Samoylov, V.: Modeling Dynamic Engineering Design Processes in PSI. In: Akoka, J., et al. (eds.) ER Workshops 2005. LNCS, vol. 3770, pp. 119–130. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Schoneneberg, H., Mans, R., Russell, N., Mulyar, N., van der Aalst, W.: Process flexibility: asurvey of contemporary approaches. In: International Workshop on CIAO/EOMAS, International Conference on Advanced Information Systems, pp. 16–30 (2008)Google Scholar
  3. 3.
    Nurcan, S.: A survey on the flexibility requirements related to business process and modeling artifacts. In: Hawaii International Conference on System Sciences, vol. 378 (2008)Google Scholar
  4. 4.
    van der Aalst, W., Weske, M., Grünbauer, D.: Case handling: a new paradigm for business process support. Data Knowl. Eng. 53(2), 129–162 (2005)CrossRefGoogle Scholar
  5. 5.
    Bergenti, F., Caire, G., Gotta, D.: Interactive workflows with WADE, WETICE (2012)Google Scholar
  6. 6.
    Jennings, N.R., Norman, T.J., Faratin, P., O’Brien, P., Odgers, B.: Autonomous agents for business process management. Applied Artificial Intelligence 14(2), 145–189 (2000)CrossRefGoogle Scholar
  7. 7.
    Casati, F., Baresi, L., Castano, S., Fugini, M.G., Mirbel, I., Pernici, B.: WIDE Workflow Development Methodology, pp. 19–28 (1999)Google Scholar
  8. 8.
    Noël, V.: Component-based software architectures and multi-agent systems: mutual and complementary contributions for supporting software development, Ph.D. Thesis (2012)Google Scholar
  9. 9.
    Weiss, G.: Multiagent systems. A modern approach to distributed artificial intelligence. The MIT Press (1999)Google Scholar
  10. 10.
    Camps, V., Gleizes, M.-P., Glize, P.: A theory of emergent computation based on cooperative self-organization for adaptive artificial systems. In: Fourth European Congress of Systems Science (1999)Google Scholar
  11. 11.
    Glize, P., Picard, G.: Self-organisation in constraint problem solving. In: Serugendo, G.D.M., Gleizes, M.-P., Karageorgos, A. (eds.) Self-organising Software from Natural to Artificial Adaptation, pp. 347–377. Springer (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Arcady Rantrua
    • 1
  • Marie-Pierre Gleizes
    • 1
  • Chihab Hanachi
    • 1
  1. 1.Institut de Recherche en Informatique de ToulouseUniversity of ToulouseToulouseFrance

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