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Constraint satisfaction with an object-oriented knowledge representation language

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Abstract

This article gives a detailed presentation of constraint satisfaction in the hybrid LAURE language. LAURE is an object-oriented language for Artificial Intelligence (AI) applications that allows the user to combine rules, constraints, and methods that cooperate on the same objects in the same program. We illustrate why this extensibility is necessary to solve some large and difficult problems by presenting a real-life application of LAURE. We describe the syntax and the various modes in which constraints may be used, as well as the tools that are proposed by LAURE to extend constraint resolution. The resolution strategy as well as some implementation details are given to explain how we obtain good performances.

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References

  1. B. Stroustrup,The C + + Programming Language Addison-Wesley: Reading, MA, 1986.

    Google Scholar 

  2. A. Goldberg, and D. Robson,Smalltalk-80: The Language and its Implementation Addison-Wesley: Reading, MA, 1983.

    Google Scholar 

  3. D. Bobrow, L. DeMichiel, R. Gabriel, S. Keene, G. Kiczales, and D. Moon, “Common Lisp object system specification,”Sigplan Notices, vol. 23, September 1988.

  4. L. Vieille, “Recursive axioms in deductive databases: The query/subquery approach,” inProc. First Int. Conf. Expert Database Syst., Charleston, 1986.

  5. Y. Caseau, “A formal system for producing demons from rules,” inProc. First Int. Conf. Deductive and Object-Oriented Databases Kyoto, Elsevier Science, 1989, pp. 188–204.

    Google Scholar 

  6. Y. Caseau, “A deductive object-oriented language,”Ann. Math. Artif. Intell. vol. 3, March 1991, pp. 211–258.

    Google Scholar 

  7. T. Imielinski, S. Naqvi, and K. Vadaparty, “Querying designs and planing databases,” inProc. Second Int. Conf. Deductive and Object-Oriented Databases Munich, Springer Verlag, LNCS 566, 1991, pp. 524–545.

    Google Scholar 

  8. T. Imielinski, S. Naqvi, and K. Vadaparty, “A query language for databases with incomplete objects,” inProc. ACM SIGMOD Int. Conf. Management of Data Atlantic City, NJ, ACM Press, May 1991.

    Google Scholar 

  9. S. Abiteboul, P. Kanellakis, and G. Grahne, “On the representation and querying of sets of possible worlds,” inProc. ACM SIGMOD, ACM Press, 1987.

  10. P. Van Hentenryck,Constraint Satisfaction in Logic Programming MIT Press: Cambridge, MA, 1989.

    Google Scholar 

  11. J. Jaffar and J. L. Lassez, “Constraint logic programming,” inProc. ACM Symp. Principles of Programming Lang. San Francisco, ACM Press, 1987.

    Google Scholar 

  12. P. Van Hentenryck, “Incremental constraint satisfaction in logic programming,” inProc. 7th Int. Conf. on Logic Programming Jerusalem, MIT Press, 1990, pp. 189–202.

    Google Scholar 

  13. N. Hentize et al., “Constraint logic programming: A reader,” inProc. 4th IEEE Symp. Logic Programming, San Francisco, 1987.

  14. Y. Caseau, “Abstract interpretation of constraints over an order-sorted domain,” inProc. Int. Logic Programming Symp. San Diego, MIT Press, October 1991, pp. 435–454.

    Google Scholar 

  15. Y. Caseau, “Constraints in an object-oriented deductive database,” inProc. Second Int. Conf. Deductive and Object-Oriented Databases Munich, Springer Verlag, LNCS 566, 1991, pp. 292–311.

    Google Scholar 

  16. P. Kanellakis, G. Kuper, and P. Revesz, “Constraint Query Language,”Proc. 9th ACM PODS, ACM Press, 1990.

  17. M. Ganti, P. Goyal, R. Nassif, and P. Sunil, “An object-oriented development environment,”COMPCON, February 1990.

  18. A. Borning, M. Maher, A. Martindale, and M. Wilson, “Constraint hierarchies and logic programming,” inProc. Sixth Int. Logic Programming Conf. Lisbon, MIT Press, June 1989, pp. 149–164.

    Google Scholar 

  19. B. Freeman-Benson, “Kaleidoscope: Mixing objects, constraints, and imperative programming,” inProc. Int. Conf. Object-Oriented Programming Syst. Lang. Appl. Ottawa, ACM Press, October 1990, pp. 77–88.

    Google Scholar 

  20. Y. Caseau and P. Koppstein, “A rule-based approach to a time-constrained traveling salesman problem,” presented at theSecond Int. Symp. Artif. Intell. Math., Fort Lauderdale, FL, January 1992, to appear.

  21. A. Borgida, R. Brachman, D. McGuinness, and L. A. Resnick, “CLASSIC: A structural data model for objects,” inACM SIGMOD Int. Conf. Management of Data Portland, OR, ACM Press, June 1989.

    Google Scholar 

  22. Y. Caseau and L. Perron, “A type system for object-oriented database programming and querying languages,” inProc. Int. Workshop on DataBase Programming Lang., Morgan Kaufmann, 1991, pp. 218–235.

  23. C. Dony, “Exception handling and object-oriented programming: Towards a synthesis, inProc. Int. Conf. Object-Oriented Programming Syst. Lang. Appl. Ottawa, ACM Press, 1990, pp. 322–330.

    Google Scholar 

  24. C. L. Forgy, “RETE: A fast algorithm for the many pattern/many object pattern matching problem,”Artificial Intelligence, no. 19, 1982.

  25. J. Mylopoulos, A. Borgida, M. Jarke, and M. Koubarakis, “Telos: a language for representing knowledge about information systems,”ACM Trans. Inf. Syst., vol. 8, no. 4, 1990.

    Google Scholar 

  26. S. Abiteboul and P. Kanellakis, “Object identity as a query language primitive,” inProc. ACM SIGMOD Conf. Management of Data, ACM Press, 1989.

  27. M. Kifer and J. Wut, “A logic for object-oriented logic programming (Maier's O-Logic revisited),” inProc. PODS-89 Philadelphia, ACM Press, 1989.

    Google Scholar 

  28. C. Lecluse and P. Richard, “Modelling complex structures in object-oriented databases,” inProc. ACM PODS, ACM Press, 1989.

  29. J. Ullman, “A comparison of deductive and object-oriented database systems,” inProc. Second Int. Conf. Deductive and Object-Oriented Databases Munich, Springer Verlag, LNCS 566, 1991, pp. 263–277.

    Google Scholar 

  30. R. Hull and J. Su, “Untyped sets, invention, and computable queries,” inProc. PODS-89 Philadelphia, ACM Press, 1989.

    Google Scholar 

  31. B. J. MacLennan, “Programming with a relational calculus,” Naval Postgraduate School, Rep no NPS52-81-013, Spetember 1981.

  32. A. Mackworth, “Consistency in networks of relations,”Artificial Intelligence vol. 8, pp. 99–118, 1977.

    Google Scholar 

  33. P. Cousot and R. Cousot, “Abstract interpretation: A unified lattice model for static analysis of programs by constructions or approximation of fixpoints,” inProc. Fourth ACM Symp. Principles of Programming Lang., ACM Press, 1977.

  34. P. Van Hentenryck and M. Dincbas, “Domains in logic programming,”Proc. AAAI-86, Philadelphia, August 1986, pp. 759–765.

  35. M. Dincbas, H. Simonis, and P. Van Hentenryck, “Extending equation solving and constraint handling in logic programming,”Colloquium on Resolution of Equation in Algebraic Structures, Austin, May 1987.

  36. P. Van Hentenryck and Y. Deville, “The cardinality operator: A new logical connective for constraint logic programming,” inProc. 8th Int. Conf. Logic Programming Paris, MIT Press, 1991, pp. 745–759.

    Google Scholar 

  37. Y. Caseau, “Efficient handling of multiple inheritance hierarchies,” inProc. Int. Conf. Object-Oriented Programming Syst., Lang. Appl. Washington, DC, ACM Press, September 1993.

    Google Scholar 

  38. Y. Caseau, P.-Y. Guillo, and E. Levenez, “A deductive and object-oriented approach to a complex scheduling problem,” inProc. Third Int. Conf. Deductive and Object-Oriented Databases Phoenix, Springer Verlag, LNCS vol. 760, December 1993, pp. 67–80.

    Google Scholar 

  39. J. F. Puget and P. Albert, “PECOS: programmation par contraintes orientée objets,”Génie Logiciel et Systèmes Experts, vol. 23, 1991.

  40. H. Aït-Kaci and A. Podelski, “The meaning of life,” PRL Research Report, DEC, Paris, 1990.

    Google Scholar 

  41. M. Ganget and B. Rosenberg, “Constraint programming and graph algorithms,” presented at theSecond Int. Symp. Artif. Intell. Math., Fort Lauderdale, FL, January 1992.

  42. W. Havens, S. Sidebottom, G. Sidebottom, J. Jones, M. Cuperman, and R. Davison, “Echnida constraint reasoning system: Next-generation expert system technology,” Simon Fraser University, Burnaby (Canada), Technical Report CSS-IS TR 90-09, December 1990.

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  1. Bellcre, 445 South Street, 07962, Morristown, NJ, USA

    Yves Caseau

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Caseau, Y. Constraint satisfaction with an object-oriented knowledge representation language. Appl Intell 4, 157–184 (1994). https://doi.org/10.1007/BF00872107

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