Accession Number : ADA172516


Title :   A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.


Descriptive Note : Doctoral thesis,


Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING


Personal Author(s) : McMannama,Jim A


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a172516.pdf


Report Date : Jun 1986


Pagination or Media Count : 314


Abstract : With the entry of Artificial Intelligence (AI) into real time applications, a rigorous analysis of AI expert systems is required in order to validate them for operational use. To satisfy this requirement for analysis of the associated knowledge representations, the techniques of formal language theory are used. A combination of theorems, proofs and problem solving techniques from formal language theory are employed to analyze language equivalents of the more commonly used AI knowledge representations of production rules (excluding working memory or situation data) and semantic networkis. Using formal language characteristics, it is shown no single support tool or automatic programming tool can ever be constructed that can handle all possible production rule or semantic network variations. Also, it is shown that the entire set of finite production-rule languages is able to be stored in and retrieval from finite semantic network languages. In effect, the semantic network structure is shown to be a viable candidate for a centralized database of knowledge. (Theses)


Descriptors :   *COMPUTER LOGIC , *ARTIFICIAL INTELLIGENCE , DATA BASES , REAL TIME , TOOLS , THEORY , PROGRAMMING LANGUAGES , THESES , PROBLEM SOLVING , MEMORY DEVICES , LANGUAGE , CENTRALIZED , COMPUTATIONAL LINGUISTICS , SYNTAX , GRAMMARS , THEOREMS , AUTOMATIC PROGRAMMING


Subject Categories : Linguistics
      Computer Programming and Software
      Computer Hardware
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE