The Power of Pluralism for Automatic Program Synthesis

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The Power of Pluralism for Automatic Program Synthesis

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Journal of the ACM (JACM) archive
Volume 29 , Issue 4 (October 1982) table of contents

Pages: 1144 - 1165

Year of Publication: 1982

ISSN:0004-5411

Author

Carl H. Smith

Department of Computer Science, University of Maryland, College Park, MD and Purdue University, West Lafayette, Indiana

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 1, Downloads (12 Months): 30, Citation Count: 31

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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, D, AND SMITH, C.H A survey of inductive reference: Methods and theory. Submitted for pubhcation
	2	BARZDIN, J.Two theorems on the limiting synthesis of functions. In Theory of Algorithms and Programs, J. Barzdin, Ed, Latvian State Umvermy, Riga, U.S.S R, 1974, pp 82-88.
	3	BLUM, L., AND BLUM, M Toward a mathematical theory of inductive inference, lnf Comrol 28 (1975), 125-155.
	4	CASE, J Periodicity in generations of automata Math. Syst. Theory 8 (1974), 15-32.
	5	CASE, J., AND NGOMANGUELLE, S. Refinements of inductive reference by poppcrian machines. Kybernettka (to appear)
	6	John Case , Carl Smith, Anomaly hierarchies of mechanized inductive inference, Proceedings of the tenth annual ACM symposium on Theory of computing, p.314-319, May 01-03, 1978, San Diego, California, United States [doi>10.1145/800133.804360]
	7	CASE, J., A~I~ SMrrn, C.Comparison of ~dentificatton criteria for machine inductive inference. Theor. Comput Sct 23, 1973.
	8	DALE~, R On the error correcting power of pluralism in inductive inference. Toeh. Pep., Computer Science Dep., Univ. of Pittsburgh, Pittsburgh, Pa, 198 l, Theor. Comput. $ci. (to appear).
	9	FELDMAN, J.Some decMability results on grammatteaI reference of best programs. Inf. Control 20 (1972), 244-262.
	10	GOLD, E.M. Language Menttficattoa in the hmtt. Inf. Control 10 (1967), 447--474.
	11	Kleene, S.On notation for ordinal numbers. J. Symbohc LogJc 3 (1938), 150-155.
	12	LAUDAN, L.Progress and Its Problems. Umverslty of Cahforma Press, Berkeley, Calif., 1977.
	13	Michael Machtey , Paul Young, An Introduction to the General Theory of Algorithms, Elsevier Science Inc., New York, NY, 1978
	14	MINICOZZl, E Some natural properties of strong-Ment~fication in inductive infe~nce. Treat. Cornput. Sc~ 2 (1976), 345-360.
	15	MUSA, J. D A theory of software rehabihty and its application. IEEE Trans. Soflw. Eng. SE.L 3 (1975), 312-327.
	16	PODNIEKS, K M. Comparing vanous concepts of funchon predietton, Part I. in Theory of Algorithms and Programs, J. Barzdln, Ed., Latvian State University, Riga, U.S.S.R., 1974~ pp. 68-81.
	17	PODNIEKS, K M. Computational complexity of predicuon strategies. In Theory of Algorithms and Programs, J. Barzdin, Ed., Latvian State University, Riga, O S.S.R, 1977 (in Russian).
	18	PUTNAM, H Piobablhty and confirmation. In Mathemancs, Matter and Method, Cambridge Universlty Press, Cambridge, England, 1975 Originally appeared in 1963 as a Voice of America l.,,eatre
	19	ROGERs, H. JIL Godel numbermgs of parUal recursive functions. ~ Symbolic Logic 23 (1958), 331-341.
	20	Hartley Rogers, Jr., Theory of recursive functions and effective computability, MIT Press, Cambridge, MA, 1987
	21	Carl Herbert Smith, Hierarchies of identification criteria for mechanized inductive inference., 1979
	22	WIEHAGEN, R., AND LIi~PE, W Characteristic properues of recognizable elassos of recursiv~ functions. Elektron. informationsverarbe#ung Kybemetlk 12 (1974), 421-438 On German).

CITED BY 31

	Thomas Zeugmann , Sandra Zilles, Learning recursive functions: A survey, Theoretical Computer Science, v.397 n.1-3, p.4-56, May, 2008
	Dana Angluin , Carl H. Smith, Inductive Inference: Theory and Methods, ACM Computing Surveys (CSUR), v.15 n.3, p.237-269, Sept. 1983
	Martin Kummer , Frank Stephan, On the structure of degrees of inferability, Proceedings of the sixth annual conference on Computational learning theory, p.117-126, July 26-28, 1993, Santa Cruz, California, United States
	Rūsiņš Freivalds , Carl H. Smith, On the role of procrastination for machine learning, Proceedings of the fifth annual workshop on Computational learning theory, p.363-376, July 27-29, 1992, Pittsburgh, Pennsylvania, United States
	Kalvis Apsītis , Rūsiņš Freivalds , Carl H. Smith, Asymmetric team learning, Proceedings of the tenth annual conference on Computational learning theory, p.90-95, July 06-09, 1997, Nashville, Tennessee, United States
	Rūsiņš Freivalds , Marek Karpinski , Carl H. Smith, Co-learning of total recursive functions, Proceedings of the seventh annual conference on Computational learning theory, p.190-197, July 12-15, 1994, New Brunswick, New Jersey, United States
	Kalvis Apsītis , Rīsiņš Freivalds , Raimonds Simanovskis , Juris Smotrovs, Closedness properties in ex-identification, Theoretical Computer Science, v.268 n.2, p.367-393, 17 October 2001
	Efim Kinber , Carl H. Smith , Mahendran Velauthapillai , Rolf Wiehagen, On learning multiple concepts in parallel, Proceedings of the sixth annual conference on Computational learning theory, p.175-181, July 26-28, 1993, Santa Cruz, California, United States
	Robert Daley , Bala Kalyanasundaram , Mahendran Velauthapillai, Breaking the probability ½ barrier in FIN-type learning, Proceedings of the fifth annual workshop on Computational learning theory, p.203-217, July 27-29, 1992, Pittsburgh, Pennsylvania, United States
	Sanjay Jain , Carl Smith , Rolf Wiehagen, On the power of learning robustly, Proceedings of the eleventh annual conference on Computational learning theory, p.187-197, July 24-26, 1998, Madison, Wisconsin, United States
	William Gasarch , Geoffrey R. Hird, Reductions for learning via queries, Proceedings of the eighth annual conference on Computational learning theory, p.152-161, July 05-08, 1995, Santa Cruz, California, United States
	William I. Gasarch , Andrew C. Y. Lee, Inferring answers to queries, Proceedings of the tenth annual conference on Computational learning theory, p.275-284, July 06-09, 1997, Nashville, Tennessee, United States
	L. Pitt, Probabilistic inductive inference, Journal of the ACM (JACM), v.36 n.2, p.383-433, April 1989
	Kalvis Apsītis , Rūsiņš Freivalds , Carl H. Smith, Choosing a learning team: a topological approach, Proceedings of the twenty-sixth annual ACM symposium on Theory of computing, p.283-289, May 23-25, 1994, Montreal, Quebec, Canada
	Robert Daley , Bala Kalyanasundaram, Capabilities of probabilistic learners with bounded mind changes, Proceedings of the sixth annual conference on Computational learning theory, p.182-191, July 26-28, 1993, Santa Cruz, California, United States
	Rusins Freivalds , Marek Karpinski , Carl H. Smith , Rolf Wiehagen, Learning by the process of elimination, Information and Computation, v.176 n.1, p.37-50, July 2002
	Andris Ambainis , Kalvis Aps&imarc;tis , R&umarc;siņs Ereivalds , Carl H. Smith, Hierarchies of probabilistic and team FIN -learning, Theoretical Computer Science, v.261 n.1, p.91-117, 06/17/2001
	Sanjay Jain , Frank Stephan , Sebastiaan A. Terwijn, Counting extensional differences in BC-learning, Information and Computation, v.188 n.1, p.127-142, 10 January 2004
	William I. Gasarch , Carl H. Smith, Learning via queries, Journal of the ACM (JACM), v.39 n.3, p.649-674, July 1992
	Andris Ambainis, Probabilistic inductive inference: a survey, Theoretical Computer Science, v.264 n.1, p.155-167, 08/06/2001
	Learning to win process-control games watching game-masters, Information and Computation, v.174 n.1, p.1-19, April 10, 2002
	Matthias Ott , Frank Stephan, Avoiding coding tricks by hyperrobust learning, Theoretical Computer Science, v.284 n.1, p.161-180, 6 July 2002
	Sanjay Jain , Efim Kinber, Learning languages from positive data and a finite number of queries, Information and Computation, v.204 n.1, p.123-175, January 2006
	Andrew C. Lee, Learning via finitely many queries, Annals of Mathematics and Artificial Intelligence, v.44 n.4, p.401-418, August 2005
	Bala Kalyanasundaram , Mahe Velauthapillai, Capabilities of Thoughtful Machines, Fundamenta Informaticae, v.74 n.2,3, p.329-340, August 2006
	William Gasarch , Mark G. Pleszkoch , Frank Stephan , Mahendran Velauthapillai, Classification using information, Annals of Mathematics and Artificial Intelligence, v.23 n.1-2, p.147-168, 1998
	Sanjay Jain , Eric Martin , Frank Stephan, Absolute versus probabilistic classification in a logical setting, Theoretical Computer Science, v.397 n.1-3, p.114-128, May, 2008
	Sanjay Jain , Efim Kinber, Iterative learning from positive data and negative counterexamples, Information and Computation, v.205 n.12, p.1777-1805, December, 2007
	William I. Gasarch , Andrew C. Y. Lee, Inferring answers to queries, Journal of Computer and System Sciences, v.74 n.4, p.490-512, June, 2008
	Lorenzo Carlucci , John Case , Sanjay Jain , Frank Stephan, Non-U-shaped vacillatory and team learning, Journal of Computer and System Sciences, v.74 n.4, p.409-430, June, 2008
	Bala Kalyanasundaram , Mahendran Velauthapillai, Taming teams with mind changes, Journal of Computer and System Sciences, v.74 n.4, p.513-526, June, 2008