The aim of the thesis is to evaluate recent work in artificial intelligence (AI). It is argued that such evaluation can be philosophically interesting, and examples are given of areas of the philosophy of AI where insufficient concentration on the actual results of AI has led to missed opportunities for the two disciplines — philosophy and AI — to benefit from cross-fertilization. The particular topic of the thesis is the use of AI techniques in psychological explanation. The claim is that such techniques can be of value in psychology, and the strategy of proof is to exhibit an area where this is the case. The field of model-based knowledge-based system (KBS) development is outlined; a type of model called a conceptual model will be shown to be psychologically explanatory of the expertise that it models. A group of major philosophies of explanation are examined, and it is discovered that such philosophies are too restrictive and prescriptive to be of much value in evaluating many areas of science; they fail to apply to scientific explanation generally. The importance of having sympathetic yardsticks for the evaluation of explanatory practices in arbitrary fields is defended, and a series of such yardsticks is suggested. The practice of providing information processing models in psychology is discussed. A particular type of model, a psychological competence model, is defined, and its use in psychological explanation defended. It is then shown that conceptual models used in model-based KBS development are psychological competence models. It follows therefore that such models are explanatory of the expertise they model. Furthermore, since KBSs developed using conceptual models share many structural characteristics with their conceptual models, it follows that a limited class of those systems are also explanatory of expertise. This constitutes an existence proof that computational processes can be explanatory of mental processes.
Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:259974 |
Date | January 1994 |
Creators | O'Hara, Kieron |
Publisher | University of Oxford |
Source Sets | Ethos UK |
Detected Language | English |
Type | Electronic Thesis or Dissertation |
Source | https://eprints.soton.ac.uk/254167/ |
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