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  Partner: UNT Libraries
 Department: Department of Computer Science
 Language: English
 Collection: UNT Theses and Dissertations
Using Normal Deduction Graphs in Common Sense Reasoning

Using Normal Deduction Graphs in Common Sense Reasoning

Date: May 1992
Creator: Munoz, Ricardo A. (Ricardo Alberto)
Description: This investigation proposes a powerful formalization of common sense knowledge based on function-free normal deduction graphs (NDGs) which form a powerful tool for deriving Horn and non-Horn clauses without functions. Such formalization allows common sense reasoning since it has the ability to handle not only negative but also incomplete information.
Contributing Partner: UNT Libraries
Visualization of Surfaces and 3D Vector Fields

Visualization of Surfaces and 3D Vector Fields

Date: August 2002
Creator: Li, Wentong
Description: Visualization of trivariate functions and vector fields with three components in scientific computation is still a hard problem in compute graphic area. People build their own visualization packages for their special purposes. And there exist some general-purpose packages (MatLab, Vis5D), but they all require extensive user experience on setting all the parameters in order to generate images. We present a simple package to produce simplified but productive images of 3-D vector fields. We used this method to render the magnetic field and current as solutions of the Ginzburg-Landau equations on a 3-D domain.
Contributing Partner: UNT Libraries
XML-Based Agent Scripts and Inference Mechanisms

XML-Based Agent Scripts and Inference Mechanisms

Date: August 2003
Creator: Sun, Guili
Description: Natural language understanding has been a persistent challenge to researchers in various computer science fields, in a number of applications ranging from user support systems to entertainment and online teaching. A long term goal of the Artificial Intelligence field is to implement mechanisms that enable computers to emulate human dialogue. The recently developed ALICEbots, virtual agents with underlying AIML scripts, by A.L.I.C.E. foundation, use AIML scripts - a subset of XML - as the underlying pattern database for question answering. Their goal is to enable pattern-based, stimulus-response knowledge content to be served, received and processed over the Web, or offline, in the manner similar to HTML and XML. In this thesis, we describe a system that converts the AIML scripts to Prolog clauses and reuses them as part of a knowledge processor. The inference mechanism developed in this thesis is able to successfully match the input pattern with our clauses database even if words are missing. We also emulate the pattern deduction algorithm of the original logic deduction mechanism. Our rules, compatible with Semantic Web standards, bring structure to the meaningful content of Web pages and support interactive content retrieval using natural language.
Contributing Partner: UNT Libraries
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