2010 Fiscal Year Final Research Report
Syntactic Approach for Efficient Identification in the Limit from Positive Data of Context-Free and Mildly Context-Sensitive Languages
| Project/Area Number |
20700124
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Intelligent informatics
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| Research Institution | Hokkaido University |
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Principal Investigator |
YOSHINAKA Ryo Hokkaido University, 大学院・情報科学研究科, 学術研究員 (80466424)
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| Project Period (FY) |
2008 – 2010
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| Keywords | 学習と知識獲得 / 計算論的学習 / 文法推論 / 形式言語理論 / 弱文脈依存言語 |
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| Research Abstract |
Recently the literature showed that context-free languages with a special property reflecting an aspect of natural language phenomena are efficiently learnable from positive data. Generalizing the preceding research, our project has presented efficient algorithms that learn from positive data even richer classes of context-free languages as well as those of mildly context-sensitive languages, which handle some non-context-free phenomena observed in natural languages. Moreover, our research project has proposed techniques that learn even more expressive classes of languages from positive data with the aid of a teacher who answers limited questions from the learner.
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