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Learning and Reasoning by Analogy: The Details

dc.date.accessioned2004-10-01T20:33:06Z
dc.date.accessioned2018-11-24T10:10:18Z
dc.date.available2004-10-01T20:33:06Z
dc.date.available2018-11-24T10:10:18Z
dc.date.issued1979-04-01en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/5732
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/5732
dc.description.abstractWe use analogy when we say something is a Cinderella story and when we learn about resistors by thinking about water pipes. We also use analogy when we learn subjects like Economics, Medicine and Law. This paper presents a theory of analogy and describes an implemented system that embodies the theory. The specific competence to be understood is that of using analogies to do certain kinds of learning and reasoning. Learning takes place when analogy is used to generate a constraint description in one domain, given a constraint description in another, as when we learn Ohm's law by way of knowledge about water pipes. Reasoning takes place when analogy is used to answer questions about one situation, given another situation that is supposed to be a precedent, as when we answer questions about Hamlet by way of knowledge about Macbeth. The input language used and the treatment of words implying CAUSE have been improved. AIM 632, "Learning New Principles from Precedents and Exercises," describes these improvements and subsequent work. It is, at this writing, in publication in the Artificial Intelligence Journal.en_US
dc.format.extent65 p.en_US
dc.format.extent19745402 bytes
dc.format.extent14151288 bytes
dc.language.isoen_US
dc.titleLearning and Reasoning by Analogy: The Detailsen_US


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