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A real-time agent model in an asynchronous-object environment

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Agents Breaking Away (MAAMAW 1996)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1038))

Abstract

To build intelligent control systems for real-life applications, we need to design software agents which combine cognitive abilities to reason about complex situations, and reactive abilities to meet hard deadlines. We propose an operational agent model which mixes AI techniques and real-time performances. Our model is based on an ATN (Augmented Transition Network) to dynamically adapt the agent's behavior to changes in the environment. Each agent uses a production system and is provided with a synchronization mechanism to avoid the possible inconsistencies of the asynchronous execution of several rule bases. Our agents communicate by message-passing and are implemented in an asynchronous-object environment. We report on the use of our agent model in intensive care patient monitoring.

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References

  1. G. Agha. Actors: a model of concurrent computation in distributed systems. Cambridge MA (USA), MIT Press 1986.

    Google Scholar 

  2. F. Barachini and R. Granec. Productions systems for process control: advances and experiences. Applied Artificial Intelligence 7: 301–316, 1993.

    Google Scholar 

  3. T. Bouron. What architecture for communication among computational agents? Report LAFORIA 92/35, November 1992.

    Google Scholar 

  4. J-P. Briot. Actalk: a testbed for classifying and designing actor languages in the Smalltalk-80 environment. Proc. of ECOOP'89, Cook, p. 109–130, 1989.

    Google Scholar 

  5. J-P. Briot. Modélisation et classification de langages de programmation concurrente à objets: l'expérience Actalk. Proc. of LMO'95, Grenoble, 1995.

    Google Scholar 

  6. S. Bussmann and Y. Demazeau. An agent model combining reactive and cognitive capabilities. Proc. of IEEE International Conference on Intelligent Robots and Systems — IROS'94, München, 1994.

    Google Scholar 

  7. F. Charpillet and A. Boyer. Incorporating AI techniques into predictable real-time systems: Reakt outcome. Proc. of 14ème journées internationales Avignon'94, Avignon, p. 121–135, 1994.

    Google Scholar 

  8. F. Charpillet and P. Théret. I.A. et temps réel. Bulletin de l'AFIA 17: 19–42, 1994.

    Google Scholar 

  9. M. Dojat and F. Pachet. NéoGanesh: an extensible Knowledge-Based System for the Control of Mechanical Ventilation. 14th IEEE-EMBS, Paris, p. 920–921, 1992.

    Google Scholar 

  10. M. Dojat M. Harf, D. Touchard M. Laforest, H. Lemaire and L. Brochard. Clinical evaluation of a knowledge-based system providing ventilatory management and decision for extubation during weaning from mechanical ventilation. American Journal of Respiratory and Critical Care Medicine: to appear, 1995.

    Google Scholar 

  11. M. Dojat and C. Sayettat. A realistic model for temporal reasoning in real-time patient monitoring. Applied Artificial Intelligence: to appear in vol. 10 n∘2, 1996.

    Google Scholar 

  12. E. H. Durfee, V. Lesser, D. D. Corkill. Coherent Cooperation Among Communicating Problem Solvers. IEEE Transactions on Computers 36(11): 1275–1291, 1987.

    Google Scholar 

  13. L. D. Erman, F. Hayes-Roth, V. Lesser. The Hearsay II speech understanding system: integrating knowledge to resolve uncertainty. ACM Computing Surveys 12 (2), 1980.

    Google Scholar 

  14. J. Ferber. Les systèmes multi-agents, vers une intelligence collective. InterEditions, Paris, 1995.

    Google Scholar 

  15. J. Ferber and J-P. Briot. Design of concurrent language for distributed artificial intelligence. Proc. of International Conference on Fifth Generation Computer Systems, Tokyo, Icot, p. 755–762, 1988.

    Google Scholar 

  16. 1992I. A. Ferguson. TouringMachines: An Architecture for Dynamic, Rational, Mobile Agents. PhD thesis, Clare Hall, University of Cambridge, UK.

    Google Scholar 

  17. L. Gasser. An Overview of DAI. In Distributed Artificial Intelligence. N. M. Avouris and L. Gasser (eds.), Klewer Academic Publisher, Boston, 1992.

    Google Scholar 

  18. A. Garvey and V. Lesser. A survey of research in deliberative real-time artificial intelligence. Journal of Real-Time Systems 6 (3): 313–347, 1994.

    Google Scholar 

  19. Z. Guessoum. Systèmes asynchrones de production. Proc. of 2ème Journées IADSMA'94, Voiron, p. 169–180, 9–11 may, 1994.

    Google Scholar 

  20. Z. Guessoum. A framework integrating an object-oriented multi-agent system and discrete event simulation. Proc. of First LAAS ICCS'95, Beirut, p. 165–173, 1995.

    Google Scholar 

  21. Z. Guessoum and R. Durand. Un système multi-agents pour modéliser l'évolution economique. Report LAFORIA, to appear, 1995.

    Google Scholar 

  22. B. Hayes-Roth. Blackboard architecture for control. A rtificial Intelligence 26: 251–321, 1985.

    Google Scholar 

  23. B. Hayes-Roth, R. Washington, D. Ash, R. Hewett, A. Collinot, A. Vina and A. Seiveur. Guardian: a prototype intelligent agent for intensive-care monitoring. Artificial Intelligence in Medicine 4: 165–185, 1992.

    Article  Google Scholar 

  24. C. Hewitt. Viewing control structures as patterns of passing messages. Artificial Intelligence 8 (3): 323–364, 1977.

    Article  Google Scholar 

  25. T. Ishida. Methods and effectiveness of parallel rule firing. IEEE Conf. on Artificial Intelligence Applications, Washington, p. 116–122, 1990.

    Google Scholar 

  26. Johnson R. How to Develop Frameworks, Tutorial notes (10), 8th ECOOP'94, Bologna, 1994.

    Google Scholar 

  27. J.P. Müller and M. Pischel. Modelling reactive behaviour in vertically layered agent architectures. Proc. of ECAI'94, p. 709–713, Amsterdam, (NL), 1994.

    Google Scholar 

  28. D. J. Musliner, J. A. Hendler, A. K. Agrawala, E. H. Durfee, J.K. Strosnider and C.J. Paul., The Challenge of Real-Time AI. Computer (January): 58–66, 1995.

    Google Scholar 

  29. H. P. Nii, N. Aiello, J. Rice. Experiments on Cage and Poligon: measuring the performance of parallel blackboard systems. Distributed Artificial Intelligence. L. Gasser and M. N. Huhns. San Mateo (Ca), Morgan Kaufmann. 2: 319–383, 1989.

    Google Scholar 

  30. F. Pachet. Représentation de connaissances par objets et règles: le système NéOpus. PhD thesis, LAFORIA, Paris 6, 1992.

    Google Scholar 

  31. F. Pachet and J-F. Perrot. Rule Firing with MetaRules. Proc. of SEKE'94, Jurmala, Latvia, p. 322–329, 1994.

    Google Scholar 

  32. F. Pachet. On the Embeddability of Production Rules in Object-Oriented Languages. Journal of Object-Oriented Programming 8(4): 19–24, 1995.

    Google Scholar 

  33. S. Quaglini, R. Bellazi, C. Brzuini, M. Stefanelli and G. Barosi. Hybrid Knowledge-Based Systems for Therapy Planning. Artificial Intelligence in Medicine 4: 207–226, 1992.

    Article  Google Scholar 

  34. Y. Shoham. Agent-Oriented Programming. Artificial Intelligence 60: 139–159, 1993.

    Article  Google Scholar 

  35. T. I. Sukuvaara, M. E. Sydänmaa, H.O. Nieminen, A. Heikelä and E. M. Koski. Object-Oriented Implementation of an Architecture for Patient Monitoring. IEEE Transactions in Biology Engineering 12 (4): 69–81, 1993.

    Article  Google Scholar 

  36. F. Wolinski. RPC-Talk: une librairie RPC-pour Smalltalk, Introduction à RPC et utilisations de RPC-Talk. Report LAFORIA 94/26, November, 1994

    Google Scholar 

  37. W. Woods. Transition Network Grammar for Natural Language Analysis. Communication of Association of Computing Machinery 13 (10): 591–606, 1970.

    Google Scholar 

  38. Y. Yokote and M. Tokoro. Experience and Evolution of Concurrent Smalltalk. Proc. of OOPSLA'87, Orlando (USA), Special issue of SIGPLAN notices, ACM, p. 406–415, 1987.

    Google Scholar 

  39. A. Yonezawa, J-P. Briot, E. Shibayama. Object-Oriented Concurrent Programming in ABCL/1. Proc. of OOPSLA'86, Portland (USA), Special issue of SIGPLAN notices, ACM, p. 258–268, 1986.

    Google Scholar 

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Author information

Authors and Affiliations

  1. Equipe OMC de J-F Perrot, LAFORIA-IBP, Université Paris 6, Boîte 169, 4, place de Jussieu, F-75252, Paris

    Z. Guessoum

  2. Faculté de Médecine, INSERM Unité 296, 8 avenue du Général Sarrail, 94010, Creteil, France

    M. Dojat

Authors
  1. Z. Guessoum
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  2. M. Dojat
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Walter Van de Velde John W. Perram

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© 1996 Springer-Verlag Berlin Heidelberg

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Guessoum, Z., Dojat, M. (1996). A real-time agent model in an asynchronous-object environment. In: Van de Velde, W., Perram, J.W. (eds) Agents Breaking Away. MAAMAW 1996. Lecture Notes in Computer Science, vol 1038. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0031856

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  • DOI: https://doi.org/10.1007/BFb0031856

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-60852-3

  • Online ISBN: 978-3-540-49621-2

  • eBook Packages: Springer Book Archive

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