Mind change speed-up for learning languages from positive data
نویسندگان
چکیده
منابع مشابه
Mind Change Speed-up for Learning Languages from Positive Data
Within the frameworks of learning in the limit of indexed classes of recursive languages from positive data and automatic learning in the limit of indexed classes of regular languages (with automatically computable sets of indices), we study the problem of minimizing the maximum number of mind changes FM(n) by a learner M on all languages with indices not exceeding n. For inductive inference of...
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In the past 40 years, research on inductive inference has developed along different lines, concerning different formalizations of learning models and in particular of target concepts for learning. One common root of many of these is Gold’s model of identification in the limit. This model has been studied for learning recursive functions, recursively enumerable languages, and recursive languages...
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ژورنال
عنوان ژورنال: Theoretical Computer Science
سال: 2013
ISSN: 0304-3975
DOI: 10.1016/j.tcs.2013.04.009