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The purpose of this study is to implement the advantages of the relatively new field of expert systems to robot kinematics. The research presented in this thesis illustrates the progress in combining the two fields. An expert system used to solve the kinematic equations of general purpose robots is presented along with some examples. / Master of Science

This dissertation deals with applications of Prolog and Artificial Intelligence (AI) to chemical engineering, and in particular, to the area of chemical process synthesis. We introduce the language Prolog (chapters 1-9), discuss AI techniques (chapters 10-11), discuss EXSEP, the EXpert System for SEParation Synthesis (chapters 12-15), and summarize applications of both AI and Artificial Neural Networks (ANNs) to chemical engineering (chapters 16-17). We have developed EXSEP, a knowledge-based system that performs separation process synthesis. EXSEP is a computer-aided design tool that can generate flowsheets using any combination of high-recovery (sharp) and low-recovery (nonsharp) separations, using a variety of separation methods with energy and mass separating agents. EXSEP generates separation process flowsheets using a unique plan-generate-test approach that incorporates computer-aided tools and techniques for problem representation and simplification, feasibility analysis of separation tasks, and heuristic synthesis and evolutionary improvement. A difficult problem in knowledge-based approaches to chemical engineering is the "quantitative or deep knowledge dilemma." Experience has shown that a strictly qualitative knowledge approach to chemical process synthesis is insufficient. However, including rigorous quantitative analysis into an expert system is cumbersome and impractical. EXSEP overcomes this deep-knowledge dilemma through a unique knowledge representation and problem-solving strategy that includes shortcut design calculations. These calculations are used as a feasibility test for all separations; no separation is chosen by EXSEP unless it is deemed as thermodynamically feasible through this quantitative, deep-knowledge, engineering analysis. We apply EXSEP for the flowsheet synthesis of several industrial separations problems. The results show that EXSEP successfully generates technically feasible and economically attractive process flowsheets accurately and efficiently. EXSEP is also user-friendly, and can be readily applied by practicing engineers using a personal computer. In addition, EXSEP is developed modularly, and can be easily expanded in the future to include additional separation methods. / Ph. D.

Call number: LD2668 .T4 1985 W94 / Master of Science

Implementing a Prolog Runtime System in a language like Java which provides its own automatic memory management and safety features such as built--in index checking and array initialization requires a consistent approach to memory management based on a simple ultimate goal: minimizing total memory management time and extra space involved. The total memory management time for Jinni is made up of garbage collection time both for Java and Jinni itself. Extra space is usually requested at Jinni's garbage collection. This goal motivates us to find a simple and practical garbage collection algorithm and implementation for our Prolog engine. In this thesis we survey various algorithms already proposed and offer our own contribution to the study of garbage collection by improvements and optimizations for some classic algorithms. We implemented these algorithms based on the dynamic array algorithm for an all--dynamic Prolog engine (JINNI 2000). The comparisons of our implementations versus the originally proposed algorithm allow us to draw informative conclusions on their theoretical complexity model and their empirical effectiveness.

Researchers have always found difficulty in attaining funding from the National Research Foundation (NRF) for new research interests. The field of Artificial Intelligence (AI) holds the promise of improving the matching of research proposals to funding sources in the area of Intelligent Information Retrieval (IIR). IIR is a fairly new AI technique that has evolved from the traditional IR systems to solve real-world problems. Typically, an IIR system contains three main components, namely, a knowledge base, an inference engine and a user-interface. Due to its inferential capabilities. IIR has been found to be applicable to domains for which traditional techniques, such as the use of databases, have not been well suited. This applicability has led it to become a viable AI technique from both, a research and an application perspective. This dissertation concentrates on researching and implementing an IIR system in LPA Prolog, that we call FUND, to assist in the matching of research proposals of prospective researchers to funding sources within the National Research Foundation (NRF). FUND'S reasoning strategy for its inference engine is backward chaining that carries out a depth-first search over its knowledge representation structure, namely, a semantic network. The distance constraint of the Constrained Spreading Activation (CSA) technique is incorporated within the search strategy to help prune non-relevant returns by FUND. The evolution of IIR from IR was covered in detail. Various reasoning strategies and knowledge representation schemes were reviewed to find the combination that best suited the problem domain and programming language chosen. FUND accommodated a depth 4, depth 5 and an exhaustive search algorithm. FUND'S effectiveness was tested, in relation to the different searches with respect to their precision and recall ability and in comparison to other similar systems. FUND'S performance in providing researchers with better funding advice in the South African situation proved to be favourably comparable to other similar systems elsewhere. / Thesis (M.Sc.)- University of Natal, Pietermaritzburg, 2001.

The purpose of this paper is to study the basic theoretic structure of intelligent data base by means of logic. There are three parts of this paper. The first part introduces the concept and relational algebra in relational data base. The second part focuses on the relationship between logic and the structure of intelligent data base and compares the intelligent database application. The last part, a SQL (Structure Query Language) queries simulation program using logic programming language Prolog, demonstrates how logic applies to query languages. / Department of Computer Science

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves [179]-199). Also available on the Internet.

Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves [179]-199). Also available on the Internet.