Angluin's theorem for indexed families of r.e. sets and applications

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Angluin's theorem for indexed families of r.e. sets and applications

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Annual Workshop on Computational Learning Theory archive
Proceedings of the ninth annual conference on Computational learning theory table of contents

Desenzano del Garda, Italy

Pages: 193 - 204

Year of Publication: 1996

ISBN:0-89791-811-8

Authors

Dick de Jongh	Institute for Logic, Language and Computation, University of Amsterdam
Makoto Kanazawa	Department of Cognitive and Information Sciences, Chiba University

Sponsors

Univ degli Studi de Milano : Universite degli Studi de Milano
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 21, Downloads (12 Months): 44, Citation Count: 10

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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.

	1	Angluin, Dana. 1980a. Finding patterns common to a set of strings. Journal of Computer System Sciences 21, 46-62
	2	Angluin, Dana. 1980b. Inductive inference of formal languages from positive data. Information and Control 45, 117-135.
	3	Blum, Leonore and Manuel Blum. 1975. Toward a mathematical theory of inductive inference. Information and Control 28, 125-155.
	4	Mark A. Fulk, Prudence and other conditions on formal language learning, Information and Computation, v.85 n.1, p.1-11, March 1990 [doi>10.1016/0890-5401(90)90042-G]
	5	Gold, E. M. 1965. Limiting recursion. Journal of Symbolic Logic 30, 28-48.
	6	Gold, E. M. 1967. Language identification in the limit. Information and Control 10~ 447-474.
	7	Jain, Sanjay and Arun Sharma. 1994. On monotonic strategies for learning r.e. languages. In Setsuo Arikawa and Klaus P. Jantke, eds, Algorithmic Learning Theory. Proceedings, 1994. Lecture Notes in Artificial Intelligence 872. Berlin: Springer.
	8	Makoto Kanazawa, Learnable classes of categorial grammars, Stanford University, Stanford, CA, 1995
	9	Shyam Kapur, Computational learning of languages, Cornell University, Ithaca, NY, 1992
	10	Efim Kinber , Frank Stephan, Language learning from texts: mindchanges, limited memory, and monotonicity, Information and Computation, v.123 n.2, p.224-241, Dec. 1995 [doi>10.1006/inco.1995.1170]
	11	Lange, Steffen, and Thomas Zeugmann. 1993. The learnabillty of recursive languages in dependence on the space of hypotheses. GOSLER-Report 20/93. Fachbereich Mathematik und Informatik, TH Leipzig.
	12	Takashi Moriyama , Masako Sato, Properties of Language Classes With Finite Elasticity, Proceedings of the 4th International Workshop on Algorithmic Learning Theory, p.187-196, November 08-10, 1993
	13	Tatsuya Motoki , Takeshi Shinohara , Keith Wright, The correct definition of finite elasticity: corrigendum to identification of unions, Proceedings of the fourth annual workshop on Computational learning theory, p.375, August 05-07, 1991, Santa Cruz, California, United States
	14	Osherson, D. N., M. Stob, and S. Weinstein. 1986. Systems That Learn. Cambridge, Mass.: MIT Press.
	15	Hartley Rogers, Jr., Theory of recursive functions and effective computability, MIT Press, Cambridge, MA, 1987
	16	Takeshi Shinohara, Inductive inference from positive data is powerful, Proceedings of the third annual workshop on Computational learning theory, p.97-110, August 06-08, 1990, Rochester, New York, United States
	17	Keith Wright, Identification of unions of languages drawn from an identifiable class, Proceedings of the second annual workshop on Computational learning theory, p.328-333, December 1989, Santa Cruz, California, United States
	18	Thomas Zeugmann , Steffen Lange, A Guided Tour Across the Boundaries of Learning Recursive Languages, Algorithmic Learning for Knowledge-Based Systems, GOSLER Final Report, p.190-258, January 1995
	19	Zeugmann, Thomas, Steffen Lange, and Shyam Kapur. 1992. Characterizations of class preserving monotonic and dual monotonic language learning. Technical Report IRCS- 92-24. Institute for Research in Cognitive Science, University of Pennsylvania.
	20	Thomas Zeugmann , Steffen Lange , Shyam Kapur, Characterizations of monotonic and dual monotonic language learning, Information and Computation, v.120 n.2, p.155-173, Aug. 1, 1995 [doi>10.1006/inco.1995.1107]

CITED BY 10

	François Denis, Learning Regular Languages from Simple Positive Examples, Machine Learning, v.44 n.1-2, p.37-66, July-August 2001
	Ganesh R. Baliga , John Case , Sanjay Jain, Synthesizing enumeration techniques for language learning, Proceedings of the ninth annual conference on Computational learning theory, p.169-180, June 28-July 01, 1996, Desenzano del Garda, Italy
	Arun Sharma , Frank Stephan , Yuri Ventsov, Generalized notions of mind change complexity, Proceedings of the tenth annual conference on Computational learning theory, p.96-108, July 06-09, 1997, Nashville, Tennessee, United States
	Sebastiaan A. Terwijn, Extensional set learning (extended abstract), Proceedings of the twelfth annual conference on Computational learning theory, p.243-248, July 07-09, 1999, Santa Cruz, California, United States
	Sanjay Jain , Steffen Lange , Jochen Nessel, On the learnability of recursively enumerable languages from good examples, Theoretical Computer Science, v.261 n.1, p.3-29, 06/17/2001
	John Case , Sanjay Jain , Arun Sharma, Synthesizing noise-tolerant language learners, Theoretical Computer Science, v.261 n.1, p.31-56, 06/17/2001
	Arun Sharma , Frank Stephan , Yuri Ventsov, Generalized notions of mind change complexity, Information and Computation, v.189 n.2, p.235-262, March 15, 2004
	Steffen Lange , Thomas Zeugmann , Sandra Zilles, Learning indexed families of recursive languages from positive data: A survey, Theoretical Computer Science, v.397 n.1-3, p.194-232, May, 2008
	Sanjay Jain , Steffen Lange , Sandra Zilles, A general comparison of language learning from examples and from queries, Theoretical Computer Science, v.387 n.1, p.51-66, November, 2007
	Sanjay Jain , Frank Stephan , Nan Ye, Prescribed learning of r.e. classes, Theoretical Computer Science, v.410 n.19, p.1796-1806, April, 2009