Meta-level Architecture for Executing Multi-agent Scenarios

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2413)


Scenarios, which constrain the behavior of agents, can be the interface between computer experts (agent system developers) and application designers (scenario writers), as well as the interface between scenario writers and agents. It raises a number of challenging issues to execute multi-agent scenarios: 1) How can scenario writers generate customized scenarios easily? 2) How can scenario writers monitor and control scenario execution so as to debug errors in scenarios? 3) How can agents negotiate for scenarios to achieve robust behavior against scenario errors? So, in this paper, we provide a web style GUI (Graphical User Interface) for scenario writers to customize scenarios. We propose a meta-level architecture for scenario writers to trace and control the execution of scenarios by observing scenarios, and for agents to negotiate with others as well as scenario writers for scenarios. The meta-level architecture is illustrated by an experimental multi-agent system of evacuation simulation.


Multiagent System Agent System Agent Agent Digital City Scenario Execution 
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.
    Bojinov, H., Casal, A., Hogg, T.: Multiagent Control of Self-reconfigurable Robots. In Proceedings of Fourth International Conference on Multiagent Systems (ICMAS 2000). pp143–150, 2000Google Scholar
  2. 2.
    Cassell, J., Bickmore, T., Billinghurst, M.: Embodiment in Conversational Interfaces: Rea CHI-99. pp520–527, 1999Google Scholar
  3. 3.
    Finin, T., Fritzson, R., McKay, D., McEntire, R.: KQML as an Agent Communication Lnguage. International Conference on Information and Knowledge Management (CIKM-94), 1994Google Scholar
  4. 4.
    Huber, M.J., Durfee, E.H.: Deciding When to Commit to Action During Observation-Based Coordination. In Proceedings of First International Conference on Multiagent Systems (ICMAS 1995). pp163–170, 1995Google Scholar
  5. 5.
    Isbister, K., Nakanishi, H., Ishida, T., Nass, C.: Helper Agent: Designing an Assistant for Human-Human Interaction in a Virtual Meeting Space. CHI-00, pp. 57–64, 2000Google Scholar
  6. 6.
    Ishida, T., Isbister K. (ed.): Digital Cities: Experiences, Technologies and Future Perspec-tives. Lecture Notes in Computer Science, 1765, Springer-Verlag, 2000Google Scholar
  7. 7.
    Ishida, T., Fukumoto M.: Interaction Design Language Q: The Initial Proposal. Transactions of JSAI, Vol 17, No. 2, pp. 166–169, 2002Google Scholar
  8. 8.
    Jonker, C.M., Treur, J.: An Agent Architecture for Multi-Attribute Negotiation. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI 01). pp. 1195–1201, 2001Google Scholar
  9. 9.
    Kitamura, Y., Yamada, T., Kokubo, T., Mawarimichi, Y., Yamamoto, T., Ishida, T.: Interactive Integration of Information Agents on the Web. Klusch, M., Zambonelli, F. (ed.): Cooperative Information Agents V, Springer-Verlag, pp. 1–13, 2001Google Scholar
  10. 10.
    Kuwabara, K., Ishida, T. and Osato, N.: AgentTalk: Describing Multi-agent Coordination Protocols with Inheritance. IEEE Conference on Tools with Artificial Intelligence (TAI-95), pp. 460–465, 1995Google Scholar
  11. 11.
    Nakanishi, H., Yoshida, C., Nishimura, T., Ishida, T.: FreeWalk: A 3D Virtual Space for Casual Meetings. IEEE Multimedia. Vol. 6, No. 2, pp. 20–28, 1999CrossRefGoogle Scholar
  12. 12.
    Oriatt, S.: Mutual Disambiguation of Recognition Errors in a Multimodal Architecture. CHI-99. pp576–583, 1999Google Scholar
  13. 13.
    Pitt, J., Mamdani, A.: A Protocol-Based Semantics for an Agent Communication Language. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI 99). pp. 486–491, 1999Google Scholar
  14. 14.
    Reeves, B., Nass, C.: The Media Equation: How People Treat Computers, Television, and New Media Like Real People and Places. Cambridge University Press, 1996Google Scholar
  15. 15.
    Sugiman, T., Misumi, J.: Development of a New Evacuation Method for Emergencies: Control of Collective Behavior by Emergent Small Groups. Journal of Applied Psychology, Vol. 73, No. 1, pp. 3–10, 1988CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  1. 1.Department of Social InformaticsKyoto UniversityJapan
  2. 2.Mathematical Systems Inc.TokyoJapan
  3. 3.Department of Social InformaticsKyoto UniversityJapan

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