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Polynomial time inference of a subclass of context-free transformations
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Source Annual Workshop on Computational Learning Theory archive
Proceedings of the fifth annual workshop on Computational learning theory table of contents
Pittsburgh, Pennsylvania, United States
Pages: 136 - 143  
Year of Publication: 1992
ISBN:0-89791-497-X
Authors
Hiroki Arimura  Department of Artificial Intelligence, Kyushu Institute of Technology, Kawazu 680-4, Iizuka 820, JAPAN
Hiroki Ishizaka  Institute for New Generation, Computer Technology, 4-28, Mita 1-chome, Minato-ku, Tokyo 108, JAPAN
Takeshi Shinohara  Department of Artificial Intelligence, Kyushu Institute of Technology, Kawazu 680-4, Iizuka 820, JAPAN
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Publisher
ACM  New York, NY, USA
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ABSTRACT

This paper deals with a class of Prolog programs, called context-free term transformations (CTF). We present a polynomial time algorithm to identify a subclass of CFT, whose program consists of at most two clauses, from positive data; The algorithm uses 2-mmg (2-minimal multiple generalization) algorithm, which is natural extension of Plotkin's least generalization algorithm, to reconstruct the pair of heads of the unknown program. Using this algorithm, we show the consistent and conservative polynomial time identifiability of the class of tree languages defined by CFTFBuniq together with tree languages defined by pairs of two tree patterns, both of which are proper subclasses of CFT, in the limit from positive data.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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H. Arimura, T. Shinohara, and S. Otsuki. Polynomial time inference of unions of tree pattern languages. In Proceedings of the Second Workshop on Algorithmic Learning Theory, pp. 105-114, 1991.
 
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G. Plotkin. A note on inductive generalization. In B. Meltzer and D. Mitchie, editors, Machine Intelligence, volume 5, pp. 153-163. Edinburgh University Press, 1970.
 
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E.Y. Shapiro. Inductive inference of theories from facts. Technical Report 192, Yale University, Department of Computer Science, 1981.
 
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T. Shinohara. Inductive inference of monotonic formal systems from positive data. In Proceedings of the First International Workshop on Algorithmic Learning Theory, pp. 339-351, 1990.
 
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Collaborative Colleagues:
Hiroki Arimura: colleagues
Hiroki Ishizaka: colleagues
Takeshi Shinohara: colleagues