Abstract

Available from UMI in association with The British Library. ;This thesis investigates the application of the theory of Conceptual Structures to an Experience Base model, which is a question-answering system for a knowledge base of pseudo-natural language statements of everyday experience. This thesis progresses to extend the fundamental principles carried from the experience base, to develop a framework for Reasoning by Analogy. Both methodologies are implemented, and uncertainty in the models is handled using the theory of Support Logic. ;Incompleteness of information, uncertainty of data and the need for a definite structure to the way in which rules and data interact, are aspects which must be dealt with if the experience base is to succeed. One more aspect is the knowledge representation which dictates the ease with which processing may be performed upon it. Conceptual graphs are used to store information used by an Experience Base. Control of the reasoning is effected by plausible inference reinforced by the theory of Support Logic for handling uncertainty. The knowledge base is a set of initially completely disparate islands of knowledge, which the system automatically clusters into coherent groups in an associative network. ;The principles evolved from research into experience bases lead to the conception, development and implementation of a computational framework for Analogical Reasoning. The reasoning is performed between domains of knowledge rather than within a single domain as in case-based reasoning, and operates on pseudo-natural language statements as for the experience base. It relies on relation-based structure mapping and includes a sophisticated mechanism for translating between the new problem and the analogue. The strong connection between this work and metaphor interpretation is also investigated, together with ideas on how to negotiate with the apparent multitude of types of analogical reasoning