This thesis describes an investigation into a proposed theory of AI. The theory postulates that a machine can be programmed to predict aspects of human behaviour by selecting and processing stored, concrete examples of previously experienced patterns of behaviour. Validity is tested in the domain of natural language. Externalisations that model the resulting theory of NLP entail fuzzy components. Fuzzy formalisms may exhibit inaccuracy and/or over productivity. A research strategy is developed, designed to investigate this aspect of the theory. The strategy includes two experimental hypotheses designed to test, 1) whether the model can process simple language interaction, and 2) the effect of fuzzy processes on such language interaction. Experimental design requires three implementations, each with progressive degrees of fuzziness in their processes. They are respectively named: Nonfuzz Babe, CorrBab and FuzzBabe. Nonfuzz Babe is used to test the first hypothesis and all three implementations are used to test the second hypothesis. A system description is presented for Nonfuzz Babe. Testing the first hypothesis provides results that show NonfuzzBabe is able to process simple language interaction. A system description for CorrBabe and FuzzBabe is presented. Testing the second hypothesis, provides results that show a positive correlation between degree of fuzzy processes and improved simple language performance. FuzzBabe's ability to process more complex language interaction is then investigated and model-intrinsic limitations are found. Research to overcome this problem is designed to illustrate the potential of externalisation of the theory and is conducted less rigorously than previous part of this investigation. Augmenting FuzzBabe to include fuzzy evaluation of non-pattern elements of interaction is hypothesised as a possible solution. The term FuzzyBaby was coined for augmented implementation. Results of a pilot study designed to measure FuzzyBaby's reading comprehension are given. Little research has been conducted that investigates NLP by the fuzzy processing of concrete patterns in language. Consequently, it is proposed that this research contributes to the intellectual disciplines of NLP and AI in general.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:341570 |
| Date | January 2000 |
| Creators | Rogers, Paul Anton Peter |
| Publisher | Bournemouth University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.bournemouth.ac.uk/306/ |
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