Thesis (Ph. D.)--University of California, Riverside, 2009. / Includes abstract. Title from first page of PDF file (viewed March 8, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 130-133). Also issued in print.

published_or_final_version / Urban Planning and Environmental Management / Master / Master of Philosophy

published_or_final_version / Industrial and Manufacturing Systems Engineering / Doctoral / Doctor of Philosophy

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This dissertation adopts an interdisciplinary approach to the field of law and artificial intelligence. It argues that the conceptual structuring of legal knowledge within an appropriate theoretical framework is of primary importance when building knowledge-based systems. While technical considerations also play a role, they must take second place to an in-depth understanding of the law. Two alternative methods of structuring legal knowledge in very different domains are used to explore the thesis. A deep-structure approach is used on nervous shock, a rather obscure area of the law of negligence. A script-based method is applied to impaired driving, a well-known part of the criminal law. A knowledge-based system is implemented in each area. The two systems, Nervous Shock Advisor (NSA) and Impaired Driving Advisor (IDA), and the methodologies they embody, are described and contrasted. In light of the work undertaken, consideration is given to the feasibility of lawyers without much technical knowledge using general-purpose tools to build knowledge-based systems for themselves.

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Much research has proven that computer controlled vegetable storage can achieve better storage conditions than traditional control systems. During the last 10 years, the use of microcomputer-based environmental control systems has become commonplace. However, to take full advantage of this computerization of the control process, it is not enough only to program the control functions that are performed by normal analog equipment. New and better control strategies must be developed. Recent advances in computer technology have made possible the development of expert systems; a branch of artificial intelligence. One of the advantages of developing such a system is that it provides a reasoning tool which approaches the level of proficiency human experts exhibit in that field. The application of new control methods using expert systems has been extensively demonstrated for greenhouse environments. However, the application of expert systems for the control of vegetable storage is still to be investigated. In the first phase of this project, the development and implementation of a sophisticated control software, using a conventional algorithm-based programming language, were achieved. Throughout the three years of experimentation in an industrial potato storage, the software proved to be appropriate for the control of storage environmental parameters (temperature and relative humidity). During the second phase, the application of an expert system for the on-line control of potato storage was explored. The development of a rule-based expert system, that could replace the conventional algorithm-based control routines was achieved. The integration of the expert system into the control software will result in a highly efficient control software, which can easily be maintained and improved as new knowledge emerges. The use of an expert system will also render possible the representation of heuristic knowledge in the form of rules, which was not possible with the use of conven

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