Towards a Framework for Agent Coordination and Reorganization, AgentCoRe

  • Mattijs Ghijsen
  • Wouter Jansweijer
  • Bob Wielinga
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4870)


Research in the area of Multi-Agent System (MAS) organization has shown that the ability for a MAS to adapt its organizational structure can be beneficial when coping with dynamics and uncertainty in the MASs environment. Different types of reorganization exist, such as changing relations and interaction patterns between agents, changing agent roles and changing the coordination style in the MAS. In this paper we propose a framework for agent Coordination and Reorganization (AgentCoRe) that incorporates each of these aspects of reorganization. We describe both declarative and procedural knowledge an agent uses to decompose and assign tasks, and to reorganize. The RoboCupRescue simulation environment is used to demonstrate how AgentCoRe is used to build a MAS that is capable of reorganizing itself by changing relations, interaction patterns and agent roles.


Multiagent System Coordination Mechanism Assignment Structure Task Structure Coordination Strategy 
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.
    So, Y., Durfee, E.: Designing organizations for computational agents. In: Prietula, M., Carley, K., Gasser, L. (eds.) Simulating Organizations, pp. 47–64. AAAI Press/MIT Press, Menlo Park (1998)Google Scholar
  2. 2.
    Carley, K.: Computational and mathematical organization theory: Perspectives and directions. Journal of Computational and Mathematical Organizational Theory (1995)Google Scholar
  3. 3.
    Cernuzzi, L., Zambonelli, F.: Dealing with adaptive multi-agent organizations in the gaia methodology. In: Müller, J.P., Zambonelli, F. (eds.) AOSE 2005. LNCS, vol. 3950, pp. 109–123. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Bernon, C., Gleizes, M., Peyruqueou, S.: Adelfe: A methodology for adaptive multi-agent systems engineering (Revised Papers). In: Petta, P., Tolksdorf, R., Zambonelli, F. (eds.) ESAW 2002. LNCS (LNAI), vol. 2577, Springer, Heidelberg (2003)CrossRefGoogle Scholar
  5. 5.
    Hübner, J.F., Sichman, J.S., Boissier, O.: S-MOISE\(^{\mbox{+}}\): A middleware for developing organised multi-agent systems. In: Boissier, O., Padget, J.A., Dignum, V., Lindemann, G., Matson, E.T., Ossowski, S., Sichman, J.S., Vázquez-Salceda, J. (eds.) AAMAS Workshops. LNCS, vol. 3913, pp. 64–78. Springer, Heidelberg (2006)Google Scholar
  6. 6.
    Newell, A.: The Knowledge Level. Artificial Intelligence 18(1), 87–127 (1982)CrossRefGoogle Scholar
  7. 7.
    Mintzberg, H.: Structures in fives: Designing effective organizations. Prentice Hall, Englewood Cliffs (1993)Google Scholar
  8. 8.
    Kitano, H., Tadokoro, S., Noda, I., Matsubara, H., Takahashi, T., Shinjou, A., Shimada, S.: Robocup-rescue: Search and rescue for large scale disasters as a domain for multi-agent research. In: Proceedings of IEEE Conference on Man, Systems, and Cybernetics(SMC-1999) (1999)Google Scholar
  9. 9.
    Uschold, M., King, M., Moralee, S., Zorgios, Y.: The enterprise ontology. The Knowledge Engineering Review (1998)Google Scholar
  10. 10.
    Zambonelli, F., Jennings, N.R., Wooldridge, M.: Organisational abstractions for the analysis and design of multi-agent systems. In: 1st International Workshop on Agent-Oriented Software Engineering at ICSE 2000 (2000)Google Scholar
  11. 11.
    Carley, K., Gasser, L.: Computational organization theory. In: Weiss, G. (ed.) Multi-Agent Systems, A Modern Approach to Distributed Artificial Intelligence, pp. 299–330. MIT Press, Cambridge (1999)Google Scholar
  12. 12.
    Jennings, N.: Coordination techniques for distributed artificial intelligence. In: O’Hare, G., Jennings, N. (eds.) Foundations of Distributed Artificial Intelligence, pp. 187–210. Wiley, Chichester (1996)Google Scholar
  13. 13.
    Tambe, M., Pynadath, D.V., Chauvat, N.: Building dynamic agent organizations in cyberspace. IEEE Internet Computing 4(2), 65–73 (2000)CrossRefGoogle Scholar
  14. 14.
    Malone, T.W., Crowston, K.: The interdisciplinary study of coordination. ACM Computing Surveys 26(1) (March 1994)Google Scholar
  15. 15.
    Lesser, V., Decker, K., Wagner, T., Carver, N., Garvey, A., Horling, B., Neiman, D., Podorozhny, R., Prasad, M.N., Raja, A., Vincent, R., Xuan, P., Zhang, X.Q.: Evolution of the GPGP/TAEMS domain-independent coordination framework. Autonomous Agents and Multi-Agent Systems 9, 87–143 (2004)CrossRefGoogle Scholar
  16. 16.
    Pynadath, D.V., Tambe, M.: Multiagent teamwork: Analyzing key teamwork theories and models. In: First Autonomous Agents and Multiagent Systems Conference (AAMAS) (2002)Google Scholar
  17. 17.
    Nair, R., Tambe, M., Marsella, S.: Team formation for reformation. In: Proceedings of the AAAI Spring Symposium on Intelligent Distributed and Embedded Systems (2002)Google Scholar
  18. 18.
    Horling, B., Benyo, B., Lesser, V.: Using self-diagnosis to adapt organization structures. In: Proceedings of the 5th International Conference on Autonomous Agents, June 2001, pp. 529–536. ACM Press, New York (2001)CrossRefGoogle Scholar
  19. 19.
    Kamboj, S., Decker, K.: Organizational self-design in semi-dynamic environments. In: 2007 IJCAI workshop on Agent Organizations: Models and Simulations (AOMS@IJCAI 2007) (2007)Google Scholar
  20. 20.
    Shehory, O., Sycara, K., Chalasani, P., Jha, S.: Agent cloning: An approach to agent mobility and resource allocation. In: IEEE CommunicationsGoogle Scholar
  21. 21.
    Martin, C., Barber, K.S.: Adaptive decision-making frameworks for dynamic multi-agent organizational change. Autonomous Agents and Multi-Agent Systems 13(3), 391–428 (2006)CrossRefGoogle Scholar
  22. 22.
    Excelente-Toledo, C.B., Jennings, N.R.: The dynamic selection of coordination mechanisms. Autonomous Agents and Multi-Agent Systems 9(1–2), 55–85 (2004)CrossRefGoogle Scholar
  23. 23.
    Rosenfeld, A., Kaminka, G.A., Kraus, S., Shehory, O.: A study of mechanisms for improving robotic group performance. Artificial Intelligence (in press)Google Scholar
  24. 24.
    Kamboj, S., Decker, K.: Organizational self-design in semi-dynamic environments. In: Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multiagent Systems (AAMAS 2007), pp. 1220–1227 (May 2007)Google Scholar
  25. 25.
    Schreiber, G., Akkermans, H., Anjewierden, A., de Hoog, R., Shadbolt, N., van de Velde, W., Wielinga, B.: Knowledge Engineering and Management: The CommonKADS Methodology. MIT Press, Cambridge (2000)CrossRefGoogle Scholar
  26. 26.
    Ghijsen, M., Jansweijer, W., Wielinga, B.: The effect of task and environment factors on M.A.S. coordination and reorganization. In: Proceedings of the Sixth International Joint Conference on Autonomous Agents and Multi-Agent Systems, short paper (to appear, 2007)Google Scholar
  27. 27.
    Dignum, V., Dignum, F., Sonenberg, L.: Towards dynamic reorganization of agent societies. In: Proceedings of CEAS: Workshop on Coordination in Emergent Agent Societies at ECAI 2004, pp. 22–27 (September 2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Mattijs Ghijsen
    • 1
  • Wouter Jansweijer
    • 1
  • Bob Wielinga
    • 1
  1. 1.Human Computer Studies Laboratory, Institute of InformaticsUniversity of Amsterdam 

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