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Berkeley Initiative in Soft Computing (BISC)

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PNL: Precisiated Natural Language

Professor Lotfi A. Zadeh

4:00 - 5:00 pm

Friday: Jan 19, 2001

60 Evans Hall

Logic colloquiums

It is a deep-seated tradition in science to view the use of natural languages in

scientific theories as a manifestation of mathematical immaturity. The rationale

for this tradition is that natural languages are lacking in precision. However,

what is not widely recognized is that adherence to this tradition carries a

steep price--the inability to exploit the richness of natural languages in a way

that lends itself to computation and automated reasoning.

In a significant departure from existing methods, the high expressive power of

natural languages is harnessed by a process termed precisiation. In essence, if

p is proposition in a natural language (NL), then precisiation of p results in a

representation of the meaning of p in the form of what is referred to as a

generalized constraint. In a generic form, a generalized constraint is expressed

as X isr R, where X is the constrained variable, R is the constraining relation

and r is a discrete-valued indexing variable whose values define the ways in

which R constrains X. In general, X, R, and r are implicit in p. Thus

precisiation of p involves explicitation and instantiation of X, R, and r.

The principal types of constraints and the associated values of r are the

following: possibilistic (r = blank); veristic (r = v); probabilistic (r = p);

usuality (r = u); random set (r = rs); fuzzy graph (r = fg); and Pawlak set (r =

ps). With these constraints serving as basic building blocks, composite

generalized constraints can be generated by combination, constraint propagation,

modification, and qualification. The set of all composite generalized

constraints and associated rules of generation and interpretation constitute the

Generalized Constraint Languages (GCL). Translation from NL to GLC is governed

by the constraint-centered semantics of natural languages (CSNL). Thus, through

CSNL, GCL serves as precisiation language for NL.

Precisiation Natural Language (PNL) is a subset of NL, which is equipped with

constraint-centered semantics and is translatable into GLC. By construction, GCL

is maximally expressive. In consequence, PNL is the largest subset of NL, which

admits precisiation. The expressive power of PNL is far greater than that of

conventional predicate-logic-based meaning-representation languages.

The concept of PNL opens the door to a significant enlargement of the role of

natural languages in scientific theories and, especially, in information

processing, decision, and control. In these and other realms, a particularly

important function that PNL can serve is that of a concept definition

language--a language that makes it possible to formulate precise definitions of

new concepts and redefine those existing concepts that do not provide a good fit

to reality.

-- Dr. Masoud NikRavesh Research Engineer - BT Senior Research Fellow Chair: BISC Special Interest Group on Fuzzy Logic and InternetBerkeley initiative in Soft Computing (BISC) Computer Science Division- Department of EECS University of California, Berkeley, CA 94720 Phone: (510) 643-4522 - Fax: (510) 642-5775 Email: nikravesh@cs.berkeley.edu URL: http://www.cs.berkeley.edu/~nikraves/ -------------------------------------------------------------------- If you ever want to remove yourself from this mailing list, you can send mail to <Majordomo@EECS.Berkeley.EDU> with the following command in the body of your email message: unsubscribe bisc-group or from another account, unsubscribe bisc-group <your_email_adress>

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