This dissertation proposes an automated system for symbolic approximate reasoning. Herein referred to as SAR, this is a further evolution of a system developed earlier by Schwartz. It is based on the concept of a linguistic variable, first introduced by Zadeh for approximate reasoning within the context of a semantics based on fuzzy sets. The present approach differs from that of Zadeh in that logical inference is defined as an operation that applies directly on linguistic terms, rather than on their underlying fuzzy set interpretations. The Schwartz system proposed two different such kinds of symbolic inference. Here three additional kinds are introduced, including one which accommodates reasoning with precise numerical information. Also developed are various appropriate modes of evidence combination. / The core of this dissertation is a full exploration of a resolution method for SAR. Termed SAR-resolution, this is an adaptation of the well-known SLD-resolution which underlies Prolog. Tasks carried out for this purpose are: (i) introduce a resolution principle for SAR, which differs from the traditional one in that it attaches a computation formula to all clauses employed, (ii) discuss resolution with evidence combination, which differs from SLD-resolution in requiring that all paths leading to the empty clause be found, (iii) define the general notion of an SAR-derivation, which specifies how a resolution process successfully terminates, (iv) fully detail the overall SAR-refutation procedure. Finally, a design for a future implementation is briefly outlined. This includes specification of the needed internal data objects and an algorithm for an inference engine written in terms of those objects. / Source: Dissertation Abstracts International, Volume: 55-09, Section: B, page: 3972. / Major Professor: Daniel G. Schwartz. / Thesis (Ph.D.)--The Florida State University, 1994.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_77268 |
| Contributors | Chung, Hsing-Tai., Florida State University |
| Source Sets | Florida State University |
| Language | English |
| Detected Language | English |
| Type | Text |
| Format | 90 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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