A Version Space Approach to Learning Context-free Grammars

作者: Kurt Vanlehn , William Ball

DOI: 10.1023/A:1022812926936

关键词:

摘要: In principle, the version space approach can be applied to any induction problem. However, in some cases representation language for generalizations is so powerful that (1) of update functions are not effectively computable, and (2) contains infinitely many generalizations. The class context-free grammars a simple exhibits these problems. This paper presents an algorithm solves both problems this domain. Given sequence strings, incrementally constructs data structure has nearly all beneficial properties space. fast enough solve small completely, it serves as framework biases permit solution larger heuristically. same basic may representations include special cases, such And-Or graphs, production systems, Horn clauses.

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