More Web Proxy on the site http://driver.im/

article

Knowledge Acquisition from Structured Data: Using Determinate Literals to Assist Search

Author:

J. Ross QuinlanAuthors Info & Claims

IEEE Expert: Intelligent Systems and Their Applications, Volume 6, Issue 6

Pages 32 - 37

https://doi.org/10.1109/64.108949

Published: 01 December 1991 Publication History

Abstract

A description is given of the FOIL (First-Order Inductive Learner) system, which exploits information from large numbers of examples to guide the search for a program. FOIL develops first-order rules from structured data described by a collection of relations. The guidance it provides turns out to be so effective that greedy search is usually adequate. Algorithms using greedy search, however, tend to suffer from a horizon effect: an action that might be desirable or even essential from a global perspective can appear relatively unpromising at a local level and so may be passed over. Rather than restricting the search space, and thus the class of learnable programs, FOIL exploits determinism to overcome some of the horizon effect of greedy search. The effect on learning time is usually negligible.

References

[1]

1. E.B. Hunt, J. Marin, and P.J. Stone, Experiments in Induction, Academic Press, New York, 1966.

[2]

2. J.R. Quinlan, "Induction of Decision Trees," Machine Learning, Vol. 1, No. 1, Mar. 1986, pp. 81-106.

Digital Library

[3]

3. L. Breiman et al., Classification and Regression Trees, Wadsworth International, Belmont, Calif., 1984.

[4]

4. B. Cestnik, I. Kononenko, and I. Bratko, "Assistant 86: A Knowledge Elicitation Tool for Sophisticated Users," in Progress in Machine Learning, I. Bratko and N. Lavrac, eds., Sigma Press, Wilmslow, U.K., 1987.

[5]

5. J.R. Quinlan and R.L. Rivest, "Inferring Decision Trees Using the Minimum Description Length Principle," Information and Computation, Vol. 80, No. 3, Mar. 1989, pp. 227-248.

[6]

6. R.S. Michalski et al., "The Multipurpose Incremental Learning System AQ15 and Its Testing Application to Three Medical Domains," Proc. Fifth Nat'l Conf. Artificial Intelligence, Morgan Kaufmann, San Mateo, Calif., 1986, pp. 1,041-1,045.

[7]

7. P. Clark and T. Niblett, "Induction in Noisy Domains," in Progress in Machine Learning, I. Bratko and N. Lavrac, eds., Sigma Press, Wilmslow, U.K., 1987.

[8]

1. J.K. Debenham, Knowledge Systems Design, Prentice Hall, Englewood Cliffs, N.J., 1989.

[9]

2. S. Marcus, ed., Automating Knowledge Acquisition for Expert Systems, Kluwer Academic Publishers, Norwell, Mass., 1989.

[10]

3. J.R. Quinlan, "Induction, Knowledge, and Expert Systems," in Artificial Intelligence Developments and Applications, J.S. Gero and R. Stanton, eds., North Holland, Amsterdam, 1988, pp. 253-271.

[11]

4. D. Michie, "Problems of Computer-Aided Concept Formation," in Applications of Expert Systems, Vol. 2, J.R. Quinlan, ed., Addison-Wesley, Reading, Mass., 1989, pp. 310-333.

[12]

5. E.Y. Shapiro, Algorithmic Program Debugging , MIT Press, Cambridge, Mass., 1983.

[13]

6. G.D. Plotkin, "A Further Note on Inductive Gereralization," in Machine Intelligence 6, B. Meltzer and D. Michie, eds., Elsevier North-Holland, New York, 1971, pp. 101-124.

[14]

7. S. Muggleton and W. Buntine, "Machine Invention of First-Order Predicates by Inverting Resolution," Proc. Fifth Int'l Conf. Machine Learning, Morgan Kaufmann, San Mateo, Calif., 1988, pp. 339-352.

[15]

8. T.M. Mitchell, "An Analysis of Generalization as a Search Problem," Proc. Sixth Int'l Joint Conf. Artificial Intelligence, Morgan Kaufmann, San Mateo, Calif., 1979, pp. 577-582.

[16]

9. J.R. Quinlan, "Learning Logical Definitions from Relations," Machine Learning, Vol. 5, No. 3, Aug. 1990, pp. 239-266.

Digital Library

[17]

10. S. Muggleton and C. Feng, "Efficient Induction of Logic Programs," Proc. First Conf. Algorithmic Learning Theory, Ohmsha, Tokyo, 1990.

[18]

11. W.J. Leech, "A Rule-Based Process Control Method with Feedback," Proc. Instrument Soc. of America Conf., Instrument Soc. of America, Research Triangle Park, N.C., 1986, pp. 169-175.

[19]

12. C. Guilfoyle, Expert Systems User, Aug. 1986, pp. 16-19.

[20]

13. H. Adeli and K.V. Balasubramanyam, "A Novel Approach to Expert Systems for Design of Large Structures," AI Magazine, Vol. 9, No. 4, 1988, pp. 54-64.

Digital Library

Cited By

Xindong W(2023)Inductive learningJournal of Computer Science and Technology10.1007/BF029394748:2(118-132)Online publication date: 22-Mar-2023
https://dl.acm.org/doi/10.1007/BF02939474
Shi SChen HMa WMao JZhang MZhang Yd'Aquin MDietze SHauff CCurry ECudre Mauroux P(2020)Neural Logic ReasoningProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3411949(1365-1374)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3340531.3411949
Prade HRichard GSerrurier M(2003)Learning first order fuzzy logic rulesProceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems10.5555/1758519.1758608(702-709)Online publication date: 30-Jun-2003
https://dl.acm.org/doi/10.5555/1758519.1758608
Show More Cited By

Recommendations

Incremental acquisition of search knowledge

The development of highly effective heuristics for search problems is a difficult and time-consuming task. We present a knowledge acquisition approach to incrementally model expert search processes. Though, experts do not normally have complete ...
Incremental knowledge acquisition for search control heuristics
Research on Cognitive Induction Based Knowledge Acquisition
IFCSTA '09: Proceedings of the 2009 International Forum on Computer Science-Technology and Applications - Volume 01

Modern Inductive Logic is an important component in inductive learning logic, which is one of the basic cognitive skills in experience knowledge acquisition. The consistency of inductive logic and inductive learning in research object and method make it ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image IEEE Expert: Intelligent Systems and Their Applications

IEEE Expert: Intelligent Systems and Their Applications Volume 6, Issue 6

December 1991

80 pages

ISSN:0885-9000

Issue’s Table of Contents

Copyright © Copyright © 1991 IEEE. All Rights Reserved.

Publisher

IEEE Educational Activities Department

United States

Publication History

Published: 01 December 1991

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

6
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 05 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Xindong W(2023)Inductive learningJournal of Computer Science and Technology10.1007/BF029394748:2(118-132)Online publication date: 22-Mar-2023
https://dl.acm.org/doi/10.1007/BF02939474
Shi SChen HMa WMao JZhang MZhang Yd'Aquin MDietze SHauff CCurry ECudre Mauroux P(2020)Neural Logic ReasoningProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3411949(1365-1374)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3340531.3411949
Prade HRichard GSerrurier M(2003)Learning first order fuzzy logic rulesProceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems10.5555/1758519.1758608(702-709)Online publication date: 30-Jun-2003
https://dl.acm.org/doi/10.5555/1758519.1758608
Kietz JDžeroski S(1994)Inductive logic programming and learnabilityACM SIGART Bulletin10.1145/181668.1816745:1(22-32)Online publication date: 1-Jan-1994
https://dl.acm.org/doi/10.1145/181668.181674
Dzeroski SLavrac N(1993)Inductive Learning in Deductive DatabasesIEEE Transactions on Knowledge and Data Engineering10.1109/69.2500765:6(939-949)Online publication date: 1-Dec-1993
https://dl.acm.org/doi/10.1109/69.250076
Džeroski SMuggleton SRussell SHaussler D(1992)PAC-learnability of determinate logic programsProceedings of the fifth annual workshop on Computational learning theory10.1145/130385.130399(128-135)Online publication date: 1-Jul-1992
https://dl.acm.org/doi/10.1145/130385.130399

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents