Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/6850
Title: Learning by Failing to Explain
Keywords: learning
explanation
heuristic parsing
design
sgraph grammars
subgraph isomorphism
Issue Date: 9-Oct-2013
Description: Explanation-based Generalization requires that the learner obtain an explanation of why a precedent exemplifies a concept. It is, therefore, useless if the system fails to find this explanation. However, it is not necessary to give up and resort to purely empirical generalization methods. In fact, the system may already know almost everything it needs to explain the precedent. Learning by Failing to Explain is a method which is able to exploit current knowledge to prune complex precedents, isolating the mysterious parts of the precedent. The idea has two parts: the notion of partially analyzing a precedent to get rid of the parts which are already explainable, and the notion of re-analyzing old rules in terms of new ones, so that more general rules are obtained.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: AITR-906
http://hdl.handle.net/1721.1/6850
Appears in Collections:MIT Items

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