BISC: Lotfi A. Zadeh: Logic colloquiums - PNL: Precisiated Natural Language

From: Masoud Nikravesh (nikravesh@eecs.berkeley.edu)
Date: Sun Jan 14 2001 - 02:47:18 MET

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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 Internet
    

    Berkeley 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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