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Timing analysis of MRL: A real-time rule-based system

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Abstract

This paper examines issues on how to predict timing behavior of rule-based decision systems for real-time applications. In particular, we focus on the analysis of response time of rule-based programs written in the production system language MRL. The design goal of MRL is to allow programmers to write OPS5-like rule-based programs in a language that is more amenable to formal analysis based on the semantic foundation underlying the language Unity. The language MRL, its analysis algorithms, and its execution system form a package of design tools for programming real-time rule-based decision systems.

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References

  1. Browne, J.C., Cheng, M.K., and Mok, A.K., 1988. Computer-aided design of real-time rule-based decision system. Technical report, Department of Computer Science, University of Texas at Austin, 1988. To appear inIEEE Transactions on Software Engineering.

  2. Chandy, K.M. and Misra, J.,Parallel Program Design: A Foundation. Reading, MA: Addison-Wesley.

  3. Forgy, C.L., 1981. OPS5 user's manual. Technical Report CMU-CS-81-135, Department of Computer Science, Carnegie-Mellon University.

  4. Forgy, C.L., 1982. Rete: A fast algorithm for the many pattern/many object pattern match problem.Artificial Intelligence, 19:17–37.

    Google Scholar 

  5. Garey, M.R. and Johnson, D.S., 1979.Computers and Interactability: A Guide to the Theory of NP-Completeness. W.H. Freeman, 1979.

  6. Haley, P.V., 1987. Real-time for RETE. InROBEXS'87: Proceedings of Conference on Robotic Expert Systems, pp. 227–282.

  7. Helly, J.J., 1984.Distributed Expert System for Space Shuttle Flight Control. PhD thesis, University of California at Los Angeles.

  8. Kligerman, E. and Stoyenko, D.A., 1986. Real-time euclid: A language for reliable real-time systems.IEEE Transaction on Software Engineering, 12:941–949.

    Google Scholar 

  9. Laffey, T.J., Cox, P.A., Schmidt, J.L., Kao, S.M., and Read, J.Y., 1988. Real-time knowledge-based systems.AI Magazine.

  10. Leinweber, D., 1987. Real-time expert systems for space applications. InProceedings of AFCEA Symposium “Space Technological Challenges for the Future”. United States Navy Academy.

  11. Lin, K.J. and Natarajan, S., 1988. Expressing and maintaining timing constraints in FLEX. InThe 11th Real-Time Systems Symposium, pp. 96–105. IEEE.

  12. Miranker, D.P., 1987. Treat: A better match algorithm for AI production systems. InProceedings of the 1987 National Conference on Artificial Intelligence.

  13. Mok, A.K., 1989. Formal analysis of real-time equational rule-based systems. InProceedings of 10th Real-Time System Symnposium. IEEE.

  14. Manna, Z. and Waldinger, R., 1985.The Logical Basis for Computing Programming, volume 1. Reading, MA: Addison-Wesley.

    Google Scholar 

  15. O'Reilly, C.A. and Cromarty, A.S., 1985. Fast is not Real-Time: Designing effective real-time AI systems.SPIE Applications of Artificial Intelligence II, 548:249–257.

    Google Scholar 

  16. Payton, D.W. and Bihari, T.E. (1991). Intelligent real-time control of robotic vehicles.Communications of the ACM, 34(8):48–63.

    Google Scholar 

  17. Perlin, M.W., 1989. The match box algorithm for parallel production system match. Technical Report CMU-CS-89-163, School of Computer Science, Carnegie Mellon University, May.

  18. Sedgewick, R., 1983.Algorithms. Reading, MA: Addison-Wesley.

    Google Scholar 

  19. Wang, C.K., 1990. MRL: The language. Technical report, Real-Time Lab, Department of Computer Sciences, University of Texas at Austin, May.

  20. Wang, C.K., 1991. Rhyme: A match algorithm for MRL. Technical report, Real-Time Lab, Department of Computer Sciences, University of Texas at Austin, October.

  21. Wang, C.K., 1992.Toward Real-Time Rule-Based Decision Systems. PhD thesis, University of Texas at Austin, August.

  22. Wright, M.L., Green, M.W., Fiegl, G., and Cross, P.F., 1986. An expert system for real-time control.IEEE Software, March 1986.

  23. Wang, C.K., Tsou, D., Wang, R.H., Browne, J.C., and Mok, A.K., 1991. Automated analysis of bounded response time for two NASA expert systems. InSIGSOFT'91 Conference on Software for Critical Systems. ACM, December.

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Authors and Affiliations

  1. Department of Computer Science, University of Texas at Austin, 78712-1188, Austin, Texas

    Chih-Kan Wang & Aloysius K. Mok

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  1. Chih-Kan Wang
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  2. Aloysius K. Mok
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Additional information

This project is partly supported by research grants from Office of Naval Research under ONR contract number N00014-89-J-1472 as well as ONR contract number N000014-89-J-1913, by a grant from Texas Advance Technology Program, and also by a grant from Texas Instruments Corporation.

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Wang, CK., Mok, A.K. Timing analysis of MRL: A real-time rule-based system. Real-Time Syst 5, 89–128 (1993). https://doi.org/10.1007/BF01088698

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