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Automata-Based Multi-agent Model as a Tool for Constructing Real-Time Intelligent Control Systems

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From Theory to Practice in Multi-Agent Systems (CEEMAS 2001)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2296))

Abstract

The multi-agent model for constructing process control intelligent systems is discussed in the paper. Agents of the model are based on three paradigms: pattern recognition, formal (string and graph) automata and rules. The efficient syntactic pattern recognition schemes are used for analysing string and graph structures that represent a structured knowledge. For string-like structures DPLL(k) quasi-context sensitive languages are applied. Graph structures are analysed with ETPL(k) graph parsers in a polynomial time. Grammatical inference algorithms can be used for both kinds of structures. It allows one to embed self-learning schemes in agents of the model.

This work was supported by the European Commission under grant ESPRIT 20288-13 Intelligent Control of Complex and Safety Critical Systems with the Help of Artificial Intelligence- and Pattern Recognition- Based Software Technologies within the European Strategic Programme for Research in Information Technology.

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References

  1. Behrens, U., FlasiƄski, M., Hagge, L., Jurek, J., Ohrenberg, K.: Recent Developments of the ZEUS Expert System ZEX, IEEE Trans. Nucl. Sci. NS-43 (1996), 65–68.

    Article  Google Scholar 

  2. Cardon, A., Lesage, F.: Toward Adaptive Information Systems, Proc. 11th Workshop Knowledge Acquisition, Modeling and Management, Banff, Alberta, Canada, April 18–23, 1998.

    Google Scholar 

  3. Correra, J.M. Laresgoiti, I., Jennings, N.R.: Using Archon, Part 2: Electricity Transportation Management, IEEE Expert 11 (1996), 71–79.

    Article  Google Scholar 

  4. FlasiƄski, M.: Towards Constructing a Self-Learning Graph Grammar-Based Pattern Recognition System, Archives of Control Sciences 37 (1992), 223–248.

    Google Scholar 

  5. FlasiƄski, M.: On the Parsing of Deterministic Graph Languages for Syntactic Pattern Recognition, Pattern Recognition 26 (1993), 1–16.

    Article  MathSciNet  Google Scholar 

  6. FlasiƄski, M.: The Programmed Grammars and Automata as Tools for a Construction of Analytic Expert Systems, Archives of Control Sciences 40 (1995), 5–35.

    Google Scholar 

  7. FlasiƄski, M.: Power Properties of NLC Graph Grammars with a Polynomial Membership Problem, Theoretical Computer Science 201 (1998), 189–231.

    Article  MathSciNet  MATH  Google Scholar 

  8. FlasiƄski, M., Jurek, J.: Dynamically Programmed Automata for Quasi Context Sensitive Languages as a Tool for Inference Support in Pattern Recognition-Based Real-Time Control Expert Systems, Pattern Recognition 32 (1999), 671–690.

    Article  Google Scholar 

  9. Guessoum, Z., Dojat, M.: A Real-Time Agent Model in an Asynchronous-Object Environment, Proc. 7th European Workshop Modelling Autonomous Agents in a Multi-Agent World, Eindhoven, The Netherlands, January 22–25, 1996.

    Google Scholar 

  10. Ingrand, F.F., Georgeff, M.P., Rao, A.S.: An Architecture for Real-Time Reasoning and System Control, IEEE Expert 7 (1992).

    Google Scholar 

  11. Jennings, N.R., Sycara, K., Wooldridge, M.: A Roadmap ofAgent Research and Development, Autonomous Agents and Mutli-Agent Systems 1 (1998), 7–38.

    Article  Google Scholar 

  12. Vincent, R., Horling, B., Lesser, V., Wagner, T.: Implementing Soft Real-Time Agent Control, Proc. 5th Intern. Conf. Autonomous Agents, Montreal, Canada, June 2001, 355–362.

    Google Scholar 

  13. Wang, H., Wang, C.: Intelligent Agents for the Nuclear Industry, IEEE Computer 30 (1997), 28–34.

    Google Scholar 

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© 2002 Springer-Verlag Berlin Heidelberg

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FlasiƄski, M. (2002). Automata-Based Multi-agent Model as a Tool for Constructing Real-Time Intelligent Control Systems. In: Dunin-Keplicz, B., Nawarecki, E. (eds) From Theory to Practice in Multi-Agent Systems. CEEMAS 2001. Lecture Notes in Computer Science(), vol 2296. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45941-3_11

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  • DOI: https://doi.org/10.1007/3-540-45941-3_11

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43370-5

  • Online ISBN: 978-3-540-45941-5

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