Skip to main content

Outline of a computational approach to meaning and knowledge representation based on the concept of a generalized assignment statement

  • Conference paper
  • First Online:
Artificial Intelligence and Man-Machine Systems

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 80))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References and related publications

  1. Ballmer, T.T., and Pinkal, M. (eds.), Approaching Vagueness. Amsterdam: North-Holland, 1983.

    Google Scholar 

  2. Bandler, W., Representation and manipulation of knowledge in fuzzy expert systems, Proc. Workshop on Fuzzy Sets and Knowledge-Based Systems, Queen Mary College, University of London, 1983.

    Google Scholar 

  3. Bartsch, R. and Vennenmann, T., Semantic Structures. Frankfurt: Attenaum Verlag, 1972.

    Google Scholar 

  4. Barwise, J. and Cooper, R., Generalized quantifiers and natural language, Linguistics and Philosophy 4 (1981) 159–219.

    Google Scholar 

  5. Bonissone, P.P., A survey of uncertainty representation in expert systems, in Proc. Second Workshop of the North-American Fuzzy Information Processing Society, General Electric Corporate Research and Development, Schenectady, NY, 1983.

    Google Scholar 

  6. Bosch, P., Vagueness, ambiguity and all the rest, in: Sprachstruktur, Individuum und Gesselschaft, Van de Velde, M., and Vandeweghe, W. (eds.). Tubingen: Niemeyer, 1978.

    Google Scholar 

  7. Brachman, R.J., What is-a is and isn't, Computer 16 (1983).

    Google Scholar 

  8. Cresswell, M.J., Logic and Languages. London: Methuen, 1973.

    Google Scholar 

  9. Czogala, E., Probabilistic Sets in Decision Making and Control. Rhineland: Verlag TUV, 1984.

    Google Scholar 

  10. Dubois, D., and Prade, H., Fuzzy cardinality and the modeling of imprecise quantification, Fuzzy Sets and Systems 16 (1985) 199–230.

    Google Scholar 

  11. Dubois, D., and Prade, H., Théorie des Possibilités, Paris: Masson, 1985.

    Google Scholar 

  12. Fox, M.S., On inheritance in knowledge representation, Proc. IJCAI (1979) 282–284.

    Google Scholar 

  13. Giles, R., Foundations for a theory of possibility, in: Fuzzy Information and Decision Processes, Gupta, M.M. and Sanchez, E. (eds.). Amsterdam: North-Holland, 183–195.

    Google Scholar 

  14. Goodman, I.R., and Nguyen, H.T., Uncertainty Models for Knowledge-Based Systems. Amsterdam: North-Holland, 1985.

    Google Scholar 

  15. Hirota, K., and Pedrycz, W., Analysis and synthesis of fuzzy systems by the use of probabilistic sets, Fuzzy Sets and Systems 10 (1983) 1–13.

    Google Scholar 

  16. Israel, D., The role of logic in knowledge representation, Computer 16 (1983) 37–41.

    Google Scholar 

  17. Kamp, H., A theory of truth and semantic representation, in Formal Methods in the Study of Language, Groenendijk, J.A. et al, (eds.), Mathematical Centre, Amsterdam, Tract 135, 1981.

    Google Scholar 

  18. Kandel, A., Fuzzy Mathematical Techniques with Applications. Reading: Addison-Wesley, 1986.

    Google Scholar 

  19. Kaufmann, A. and Gupta, M., Introduction to Fuzzy Arithmetic. New York: Van Nostrand, 1985.

    Google Scholar 

  20. Keenan, E., (ed.). Formal Semantics of Natural Language. Cambridge: Cambridge University Press, 1975.

    Google Scholar 

  21. Lambert, K., and van Fraassen, B.C., Meaning relations, possible objects and possible worlds, Philosopical Problems in Logic (1970) 1–19.

    Google Scholar 

  22. Mamdani, E.H., and Gaines, B.R., Fuzzy Reasoning and its Applications. London: Academic Press, 1981.

    Google Scholar 

  23. McDermott, D., and Cherniak, E., Introduction to Artificial Intelligence. Reading: Addison-Wesley, 1985.

    Google Scholar 

  24. Moore, R.C., Problems in Logical Form, SRI Tech. Report 241, Menlo Park, 1981.

    Google Scholar 

  25. Moore, R.C., The role of logic in knowledge representation and commonsense reasoning, Proc. AAAI (1982) 428–433.

    Google Scholar 

  26. Nilsson, N., Principles of Artificial Intelligence, Palo Alto: Tioga Press, 1980.

    Google Scholar 

  27. Ralescu, D., Toward a general theory of fuzzy variables, Journ. Math. Analysis and Appl. 86 (1982) 176–193.

    Google Scholar 

  28. Rich, C., Knowledge representation languages and predicate calculus: how to save your cake and eat it too, Proc. AAAI (1982) 192–196.

    Google Scholar 

  29. Scheffler, I., A Philosophical Inquiry into Ambiguity, Vaguenss and Metaphor in Language. London: Routledge & Kegan Paul, 1981.

    Google Scholar 

  30. Tarski, A., Logic, Semantics, Metamathematics. Oxford: Clarendon Press, 1956.

    Google Scholar 

  31. van Fraassen, B.C., Formal Semantics and Logic. New York: Macmillan, 1971.

    Google Scholar 

  32. Wahlster, W., Hahn, W.V., Hoeppner, W., and Jameson, A., The anatomy of the natural language dialog system HAM-RPM, in: Natural Language Computer Systems, Bolc, L., (ed.). Amsterdam: North-Holland, 205–233, 1976.

    Google Scholar 

  33. Yager, R., Reasoning with fuzzy quantified statements — I, Kybernetes 14 (1985) 233–240.

    Google Scholar 

  34. Yager, R., Set Based Representation of Conjunctive and Disjunctive Knowledge, Machine Intelligence Institute Tech. Rep. #M11-604, Iona College, New Rochelle, NY, 1986.

    Google Scholar 

  35. Zadeh, L.A., A fuzzy-set-theoretic interpretation of linguistic hedges, Journal of Cybernetics 2 (1972) 4–34.

    Google Scholar 

  36. Zadeh, L.A., PRUF — a meaning representation language for natural languages, Int. J. Man-Machine Studies 10 (1978) 395–460.

    Google Scholar 

  37. Zadeh, L.A., Fuzzy sets and information granularity, in Advances in Fuzzy Set Theory and Applications (Gupta, M., Ragade, R. and Yager, R., eds.). Amsterdam: North-Holland, 3–18, 1979.

    Google Scholar 

  38. Zadeh, L.A., Test-score semantics for natural languages and meaning-representation via PRUF, Tech. Note 247, AI Center, SRI International, Menlo Park, CA, 1981. Also in: Empirical Semantics, Rieger, B.B., (ed.). Bochum: Brockmeyer, 281–349, 1981.

    Google Scholar 

  39. Zadeh, L.A., Possibility theory as a basis for meaning representation, in: Proc. of the Sixth Wittgenstein Symposium, Leinfellner, W., et al, (eds.), Kirchberg, 253–261, 1982.

    Google Scholar 

  40. Zadeh, L.A., A Computational Approach to Fuzzy Quantifiers in Natural Languages, Computers and Mathematics 9 (1983) 149–184.

    Google Scholar 

  41. Zadeh, L.A., A fuzzy-set-theoretic approach to the compositionality of meaning: Propositions, dispositions and canonical forms, Journal of Semantics 3 (1983) 253–272.

    Google Scholar 

  42. Zadeh, L.A., The role of fuzzy logic in the management of uncertainty in expert systems, Fuzzy Sets and Systems 11 (1983) 199–227.

    Google Scholar 

  43. Zadeh, L.A., Syllogistic reasoning in fuzzy logic and its application to usuality and reasoning with dispositions, IEEE Transactions on Systems, Man and Cybernetics SMC-15 (1985) 754–763.

    Google Scholar 

  44. Zimmermann, J., Fuzzy Set Theory-and its Applications. Boston: Kluwer, 1985.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Heinz Winter

Rights and permissions

Reprints and permissions

Copyright information

© 1986 Springer-Verlag

About this paper

Cite this paper

Zadeh, L.A. (1986). Outline of a computational approach to meaning and knowledge representation based on the concept of a generalized assignment statement. In: Winter, H. (eds) Artificial Intelligence and Man-Machine Systems. Lecture Notes in Control and Information Sciences, vol 80. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0006964

Download citation

  • DOI: https://doi.org/10.1007/BFb0006964

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-16658-0

  • Online ISBN: 978-3-540-39840-0

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics