ACM Home Page
Please provide us with feedback. Feedback
Angluin's theorem for indexed families of r.e. sets and applications
Full text PdfPdf (1.36 MB)
Source 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): 2,   Downloads (12 Months): 13,   Citation Count: 10
Additional Information:

references   cited by   index terms   collaborative colleagues   peer to peer  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/238061.238095
What is a DOI?

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
 
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
 
9
 
10
 
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
 
13
 
14
Osherson, D. N., M. Stob, and S. Weinstein. 1986. Systems That Learn. Cambridge, Mass.: MIT Press.
 
15
 
16
 
17
 
18
 
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

CITED BY  10
 
 
 
 
 
 
 

Collaborative Colleagues:
Dick de Jongh: colleagues
Makoto Kanazawa: colleagues

Peer to Peer - Readers of this Article have also read: