A Non-Cognitive Formal Approach to Knowledge Representation in Artificial Intelligence.
AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING
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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
- Computer Programming and Software
- Computer Hardware