Polynomial learnability and Inductive Logic Programming: Methods and results
Publication
, Journal Article
Cohen, WW; Page, CD
Published in: New Generation Computing
December 1, 1995
Over the last few years, the efficient learnability of logic programs has been studied extensively. Positive and negative learnability results now exist for a number of restricted classes of logic programs that are closely related to the classes used in practice within inductive logic programming. This paper surveys these results, and also introduces some of the more useful techniques for deriving such results. The paper does not assume any prior background in computational learning theory. © 1995 Ohmsha, Ltd. and Springer.
Duke Scholars
Published In
New Generation Computing
DOI
EISSN
1882-7055
ISSN
0288-3635
Publication Date
December 1, 1995
Volume
13
Issue
3-4
Start / End Page
369 / 409
Related Subject Headings
- Information Systems
- 46 Information and computing sciences
- 40 Engineering
- 1702 Cognitive Sciences
- 0803 Computer Software
- 0801 Artificial Intelligence and Image Processing
Citation
APA
Chicago
ICMJE
MLA
NLM
Cohen, W. W., & Page, C. D. (1995). Polynomial learnability and Inductive Logic Programming: Methods and results. New Generation Computing, 13(3–4), 369–409. https://doi.org/10.1007/BF03037231
Cohen, W. W., and C. D. Page. “Polynomial learnability and Inductive Logic Programming: Methods and results.” New Generation Computing 13, no. 3–4 (December 1, 1995): 369–409. https://doi.org/10.1007/BF03037231.
Cohen WW, Page CD. Polynomial learnability and Inductive Logic Programming: Methods and results. New Generation Computing. 1995 Dec 1;13(3–4):369–409.
Cohen, W. W., and C. D. Page. “Polynomial learnability and Inductive Logic Programming: Methods and results.” New Generation Computing, vol. 13, no. 3–4, Dec. 1995, pp. 369–409. Scopus, doi:10.1007/BF03037231.
Cohen WW, Page CD. Polynomial learnability and Inductive Logic Programming: Methods and results. New Generation Computing. 1995 Dec 1;13(3–4):369–409.
Published In
New Generation Computing
DOI
EISSN
1882-7055
ISSN
0288-3635
Publication Date
December 1, 1995
Volume
13
Issue
3-4
Start / End Page
369 / 409
Related Subject Headings
- Information Systems
- 46 Information and computing sciences
- 40 Engineering
- 1702 Cognitive Sciences
- 0803 Computer Software
- 0801 Artificial Intelligence and Image Processing