Abstract
It is suggested that communication between humans — as well as between humans and machines — may be made more precise by the employment of a meaning representation language PRUF which is based on the concept of a possibility distribution. A brief exposition of PRUF is presented and its application to precisiation of meaning is illustrated by a number of examples.
Computer Science Division, Department of Electrical Engineering and Computer Sciences and the Electronics Research Laboratory, University of California, Berkeley, California 94720. Research supported by the National Science Foundation Grants IST8018196 and MCS79-06543.
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Zadeh, L.A. (1984). Precisiation of Meaning via Translation into PRUF. In: Vaina, L., Hintikka, J. (eds) Cognitive Constraints on Communication. Synthese Language Library, vol 18. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-9188-6_21
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