| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2017: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Outline of Final Research Achievements |
In recent years, approaches genericallly called ``distirbutional learning'' towards learning mildly context-sensitive languages have been making many positive results. Our project developped the theory of ``distributional learning'' further and tackled learning even more complex grammar formalisms. We gave a uniform view on those existing learning algorithms for mildly context-sensitive languages and derived a general condition with which a grammar formalism shall be distributionally learnable. We targeted grammar formalisms more complex than mildly context-sensitive grammars, including conjunctive grammars, which may define the intersection of languages, and non-linear lambda grammars, which have copying production rules. Furthermore, we have succeeded in weakening the two representative conditions that make grammars distributionally learnable and showed that even richer classes of languages than those used to be defined are distributionally learnable.
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