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A generic model of cognitive agent to develop open systems

  • Distributed AI and Multi-Agent Systems I
  • Conference paper
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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1159))

Abstract

The paper presents an approach to building multi-agent systems. We are interested in complex agents able to reason about their tasks, and to display a proactive behavior, when installed on a network of heterogeneous computers. We developed the concept of a generic agent (GAg), equipped with the basic communication and ”mental” structure, but ignorant, i.e., not containing any application expertise, nor having any knowledge about the external world. When building an application, actual agents are cloned from the generic agent. In addition, a specific environment, OSACA (Open System for Asynchronous Cognitive Agents), simplifies the process of creating agents on a network of heterogeneous machines. The paper discusses mainly the basic structure of the generic agent. Our approach is also illustrated with a small example of an agent which helps writing a technical paper in a research laboratory...

Supported by CAPES/Brazil, grant number 1307/94.

On leave from CEFET-PR, Brazil and supported by CITS/CNPq, grant number 260139/92.

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References

  1. Barthès J-P., (1994), Developing Integrated Object Environment for Building Large Knowledge Based Systems, Int. J. Human-Computer Studies, vol 41, pp. 33–58.

    Google Scholar 

  2. Bond H., Gasser L. (1988), What is DAI ?, Reading in DAI, Morgan Kaufman Publishers.

    Google Scholar 

  3. Brooks R. A., (1991), Intelligence without representation, AI, vol 47, pp. 139–159.

    Google Scholar 

  4. Cockburn D., Jennings N. R., (1995), ARCHON: A Distributed Artificial Intelligence System for Industrial Applications, in O'Hara G.M.P., Jennings N.R., ed., Foundations of DAI, Wiley.

    Google Scholar 

  5. de Azevedo H., Scalabrin E. E., Barthès J-P. A., (1995), Capitalisation des Connaissances d'un Groupe de Recherche à l'Aide d'une Population d'Agents Cognitifs, 3mes Journées Francophones IAD and SMA, St Baldoph, pp. 193–205.

    Google Scholar 

  6. Ferber J., Drogoul A., (1992), Using Reactive Multi-Agent Systems in Simulation and Problem Solving, in Avouris N.M., Gasser L., eds., Distributed Artificial Intelligence: Theory and Praxis, Kluwer Academic Publishers, pp. 53–80.

    Google Scholar 

  7. Finin T., Weber J., Wiederhold G., Genesereth M., Fritzson F., McKay D., McGuire J., Pelavin P., Shapiro S., (1993), Specification of the KQML Agent-Communication Language, Technical Report EIT TR 92-04, Enterprise Integration Technologies, Palo Alto, CA, Updated in July.

    Google Scholar 

  8. Gasser L., Braganza C., Herman N., (1987), MACE: a Flexible Testbed for Distributed AI Research, in Huhns M.N., eds., Distributed Artificial Intelligence, Vol. 1, Pitman Publishing, London, pp. 119–152.

    Google Scholar 

  9. Genesereth M. R., Ketchpel S. P., (1994), Software Agents, Communications of the ACM, vol 37(7), July, pp. 48–53.

    Google Scholar 

  10. Hayes-Roth B., (1995), An Architecture for Adaptative Intelligent Systems, Artificial Intelligence, vol 72, pp. 329–365.

    Google Scholar 

  11. Kolb M., (1995), CooL Specification, Technical Report, SIEMENS AG.

    Google Scholar 

  12. Kuokka D., Harada L., (1995), Matchmaking for information agents, Proceedings of the Joint Conference on Artificial Intelligence.

    Google Scholar 

  13. McGuire J., Kuokka D., Weber L., Tenenbaum J., Gruber T., Olsen G, (1993), SHADE: Technology for knowledge-based Collaborative Engineering, Concurrent Engineering Research and Application, vol 1(3).

    Google Scholar 

  14. Nishida T., Takeda H., (1993), Towards the knowledgeable community, Proceedings of the International Conference on Building and Sharing of Very Large-Scale Knowledge Bases, Japan Information Processing Development Center, Tokyo.

    Google Scholar 

  15. Scalabrin E. E., Barthès J-P. A., (1996), OSACA 1.0: A Primer, Technical Report, Memo UTC/GI/DI/N 121, January.

    Google Scholar 

  16. Scalabrin, E. E., Barthès, J-P. A., (1993), OSACA: une architecture ouverte d'agents cognitifs indépendants, PRC-IA, Montpellier.

    Google Scholar 

  17. Singh N., (1994), A Common Lisp API and Facilitator for ABSI, Report Logic-93-4, Logic Group, Computer Science Departement, Stanford University, March.

    Google Scholar 

  18. Smith R. G., (1980), The Contract Net Protocol: High-Level Communication and Control in a Distributed Problem Solver, IEEE Trans. on Computers, C29(12), pp. 1104–1113.

    Google Scholar 

  19. Wooldridge M. J., Jennings N. R., (1994), Agent Theories, Architectures, and Languages: A Survey, Workshop on Agent Theories, Architectures and Languages, ECAI'94, Amsterdam.

    Google Scholar 

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Díbio L. Borges Celso A. A. Kaestner

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© 1996 Springer-Verlag Berlin Heidelberg

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Scalabrin, E.E., Vandenberghe, L., de Azevedo, H., Barthès, J.P.A. (1996). A generic model of cognitive agent to develop open systems. In: Borges, D.L., Kaestner, C.A.A. (eds) Advances in Artificial Intelligence. SBIA 1996. Lecture Notes in Computer Science, vol 1159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61859-7_7

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  • DOI: https://doi.org/10.1007/3-540-61859-7_7

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-61859-1

  • Online ISBN: 978-3-540-70742-4

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