| Aamodt, A.: Knowledge Acquisition and Learning by Experience -- The Role of Case-Specific Knowledge. In Tecuci, G., Kodrato#, Y., eds.: Machine Learning and Knowledge Acquisition -- Integrated Approaches. Academic Press (1995) 197--245 |
....CAP (Mitchell et al. 1994) They mostly use the training example specification and oracle interaction to guide an empirical learning from examples approach, as well as relying significantly on learning by watching the user. Case based reasoning systems like PROTOS (Porter et al. 1990) CREEK (Aamodt, 1995), and CABINS (Sykara and Miyashita, 1995) rely heavily on various types of interactions with the user (primarily knowledge specification, training example specification, and oracle interaction, but also explanations in the case of Protos) In that respect they are very similar to 19 the Disciple ....
Aamodt A. (1995). Knowledge Acquisition and Learning by Experience - The Role of CaseSpecific Knowledge. In G. Tecuci and Y. Kodratoff (Eds.), Machine Learning and Knowledge Acquisition: Integrated Approaches. New York: Academic Press.
.... activate hypotheses and select hypothesis . The former of these is realized by the primitive method activate , while explain and focus primitives collectively realize the select hypothesis subtask. The activate explain focus cycle is a general mechanism modeled in the Creek system [Aamodt 95] and realizes the abduction of the most promising hypothesis on the basis of the case based reasoning paradigm. The utilization of context for improving abductive efficiency goes hand in hand with improving the retrieval of better cases [ zturk 97] The case based method of Creek relies heavily ....
Aamodt, A. Knowledge acquisition and learning by experience-the role of case specific knowledge, in Machine learning and knowledge acquisition, Tecuci,G and Kodratoff, Y (eds), Academic press, 1995, pp 197-245.
....method can lead to an improvement in accuracy and comprehensibility. 1 Introduction The recent progress in Case Based Reasoning has shown that one of the most important challenges in developing future AI methods will be to combine and synergistically utilize general and case based knowledge (Aamodt 1995). The presented approach has an origin in Riesbeck and Schank s psychological consideration (Riesbeck Schank 1989, pp.11) When an activity has been repeated often enough it becomes rule like in nature. We do not reason from prior cases when well establish rules are available. When the ....
Aamodt, A. (1995). Knowledge Acquisition and Learning by Experience - The Role of CaseSpecific Knowledge. In Kodratoff, Y., Tecuci, G. (eds.) On Integration of Knowledge Acquisition and Machine Learning. Academic Press (in press).
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Aamodt A., Knowledge acquisition and learning by experience - the role of case specific knowledge, in Machine Learning and Knowledge Acquisition, Academic Press 1995, ISBN 0-12-685120-4, pp. 197-245.
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Aamodt, A.: Knowledge Acquisition and Learning by Experience -- The Role of Case-Specific Knowledge. In Tecuci, G., Kodrato#, Y., eds.: Machine Learning and Knowledge Acquisition -- Integrated Approaches. Academic Press (1995) 197--245
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Agnar Aamodt. Knowledge Acquisition and Learning by Experience -- The Role of Case-Specific Knowledge. In G. Tecuci and Y. Kodratoff, editors, Machine Learning and Knowledge Acquisition -- Integrated Approaches, chapter 8, pages 197--245. Academic Press, 1995.
No context found.
Agnar Aamodt. Knowledge Acquisition and Learning by Experience -- The Role of Case-Specific Knowledge. In G. Tecuci and Y. Kodratoff, editors, Machine Learning and Knowledge Acquisition -- Integrated Approaches, chapter 8, pages 197--245. Academic Press, 1995.
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