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Achieving efficient cooperation in a multi-agent system: the twin-base modeling

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Cooperative Information Agents (CIA 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1202))

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Abstract

The Virtual Secretary 2 project (ViSe2) focuses on the construction of a multi-agent cooperation system. As a research vehicle, we have chosen to build intelligent agents that perform secretarial tasks for their users either by themselves or via cooperation. An individual ViSe2 agent has limited knowledge and problem-solving capabilities. To act better for its user, the agent interacts with other peers to solve problems. In this sense, an agent's ability to reason about the other agents' activities and thus find the peer becomes a key issue. In this paper, we propose a twin-base (cooperator-base ⊎ task-base) modeling for efficient cooperation in a small agent group. The cooperator-base collects stable information of the others and acts as an auxiliary base to the task-base. The task-base provides direct mappings between tasks and relevant expert agents that can perform such tasks. A capability revision process is proposed for keeping the mapping information consistent. With such twin-base modeling, when an agent receives a task that is beyond its capabilities, the agent can directly retrieve the best qualified peer from its task-base, and ask the peer to perform the task. To test the validation of the twin-base modeling, we have implemented a prototype of ViSe2 multi-agent cooperation system. The experimental results show that the system achieves the anticipated functionality: an individual agent performs the user's task by either retrieving results from its local knowledge base system, or consulting peer agents to take over the job. More precisely, to verify our intuition that the twin-base modeling achieves efficient cooperation, we compare the performance of our model with other cooperation approaches, i.e., the contract net protocol [2], the assisted coordination approach [4], and the acquaintance model approach [14, 7]. Results received so far indicate that our method achieves the most efficient cooperation with high on-line performance.

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References

  1. Cao, W., Bian, C. G., and Hartvigsen, G.: Cooperator-Base ⊎ Task-Base for Agent Modeling: the Virtual Secretary Approach. In Proceedings of AAAI-96 Workshop on Agent Modeling, pages 105–111, Portland, Oregon, USA. AAAI Press, August 1996.

    Google Scholar 

  2. Davis, R. and Smith, R. G.: Negotiation as a Metaphor for Distributed Problem Solving. Artificial Intelligence 20(1): pages 63–109, 1983.

    Google Scholar 

  3. Expert Interface Technologies: Tix — Programming Library for the Tk Toolkit, Version 4.0. URL: http://www.xpi.com/tix/. 1995.

    Google Scholar 

  4. Genesereth, M. R. and Ketchpel, S. P.: Software Agents. Communication of the ACM 37(7): pages 48–53, 1994.

    Google Scholar 

  5. Hartvigsen, G., Johansen, S., Helme, A., Widding, R. A., Bellika, G., Cao, W.: The Virtual Secretary Architecture for Secure Software Agents. In Proceedings of the First International Conference on the practical Application of Intelligent Agents and Multi-Agent Technology (PAAM'96), pages 843–851, London, U.K. The Practical Application Company Ltd, April 1996.

    Google Scholar 

  6. Jain, R.: The Art of Computer Systems Performance Analysis. John Wiley and Sons, 1991.

    Google Scholar 

  7. Jennings, N.: Cooperation in Industrial Multi-agent Systems. World Scientific, 1994.

    Google Scholar 

  8. Klusch, M., Scheew, O. and Grossmann, B.: Interactive Development Environment for Agent System. URL: ftp://ftp.informatik.uni-kiel.de/pub/kiel/ideas, Christian-Albrechts University of Kiel, Germany, 1995.

    Google Scholar 

  9. Lashkari, Y., Metral, M. and Maes, P.: Collaborative Interface Agents. In Proceedings of the Twelfth National Conference on Artificial Intelligence. AAAI Press, 1994.

    Google Scholar 

  10. Lehenbauer, K. and Diekhans, M.: Extended Tcl (TclX), Version 7.4a. URL: ftp://ftp.cs.berkeley.edu:/ucb/tcl/. NeoSoft Company, 1995.

    Google Scholar 

  11. Ousterhout, J.: The Tcl and Tk Toolkit, Tcl Version 7.4, Tk Version 4.0. URL: http://www.sunlabs.com/research/tcl, The University of California at Berkeley, 1995.

    Google Scholar 

  12. Smith, R.G. and Davis, R.: Frameworks for Cooperation in Distributed Problem Solving. IEEE Transaction on Systems, Man and Cybernetics 11(1): pages 61–70, 1981.

    Google Scholar 

  13. Tarau, P.: BinProlog 4.00 Software and BinProlog 4.00 User Guide. URL: ftp://clement.info.umoncton.ca/pub/BinProlog, 1995.

    Google Scholar 

  14. Wittig, T.: ARCHON — an architecture for multi-agent systems. Ellis Horwood, 1992.

    Google Scholar 

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Peter Kandzia Matthias Klusch

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© 1997 Springer-Verlag Berlin Heidelberg

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Cao, W., Bian, CG., Hartvigsen, G. (1997). Achieving efficient cooperation in a multi-agent system: the twin-base modeling. In: Kandzia, P., Klusch, M. (eds) Cooperative Information Agents. CIA 1997. Lecture Notes in Computer Science, vol 1202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62591-7_35

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  • DOI: https://doi.org/10.1007/3-540-62591-7_35

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  • Print ISBN: 978-3-540-62591-9

  • Online ISBN: 978-3-540-68321-6

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