: J.G. Carbonell. Learning by analogy: forming and generalizing plans from past experience in Michalski, R.S., Carbonell, J.G., Mitchell, T.M., (eds): Machine Learning: An Artificial Intelligence Approach pp.137-160 (Tioga Press 1983). Home/Search Document Not in Database Summary Related Articles Check |
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The Specialization and Transformation of Constructive.. - Peter Madden Department (1989) (2 citations) (Correct)
....by transforming the associated proofs. The main idea taken from analogy related research consists of the transformation of successful solution sequences to past problems into successful solution sequences to current similar problems by the application of transformation rules or operators, Carbonell 83 and Carbonell 85] The domain of recursive algorithms is a good one in which to adopt this transformative analogy approach since the inductive proofs which synthesize the algorithms generally share a high degree of structural similarity [Madden 87] The crucial element in the transformation is ....
: J.G. Carbonell. Learning by analogy: forming and generalizing plans from past experience in Michalski, R.S., Carbonell, J.G., Mitchell, T.M., (eds): Machine Learning: An Artificial Intelligence Approach pp.137-160 (Tioga Press 1983).
A summary for the application to the 1988 Alvey - Conference Peter Madden (Correct)
....be applied to a past successful proof plan, the source, in order to map a proof plan, the target, which guides the construction of a new proof yielding a new program. Indeed, the optimization of several sorting algorithms is a sub domain of this wider application of transformative analogy (cf. Carbonell [1983, 1985] and Madden [1987] ....
: J.G. Carbonell. Learning by analogy: forming and generalizing plans from past experience in Michalski, R.S., Carbonell, J.G., Mitchell, T.M., (eds): Machine Learning: An Artificial Intelligence Approach pp.137-160 (Tioga Press 1983).
The Specialization of Constructive Existence Proofs - Peter Madden October (1988) (Correct)
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: J.G. Carbonell. Learning by analogy: forming and generalizing plans from past experience in Michalski, R.S., Carbonell, J.G., Mitchell, T.M., (eds): Machine Learning: An Artificial Intelligence Approach pp.137-160 (Tioga Press 1983).
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