Hybrid abductive inductive learning: A generalisation of progol

Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

Volumn 2835, Issue , 2003, Pages 311-328

  Ray, Oliver ^a   Broda, Krysia ^a   Russo, Alessandra ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; FORMAL LOGIC; LOGIC PROGRAMMING; MATHEMATICAL OPERATORS; SEMANTICS; SET THEORY; COMPUTATION THEORY; COMPUTER CIRCUITS; LEARNING SYSTEMS; PRECIPITATION (METEOROLOGY); RECONFIGURABLE HARDWARE;

ABDUCTIVE LOGIC PROGRAMMING (AGP); INDUCTIVE LOGIC PROGRAMMING (ILP); KERNEL GENERALIZATION; SKOLEM CONSTANTS; ABDUCTIVE LOGIC PROGRAMMING; GENERALISATION; INDUCTIVE LEARNING; INFERENCE METHODS; NEW APPROACHES; PROOF PROCEDURES; SINGLE SEEDS;

LEARNING SYSTEMS; INDUCTIVE LOGIC PROGRAMMING (ILP);

EID: 9444260997     PISSN: 03029743     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-540-39917-9_21     Document Type: Conference Paper

References (17)

1. C. Chang and R.C. Lee. Symbolic Logic and Mechanical Theorem Proving. Academic Press, 1973.
2. K. Furukawa and T. Ozaki. On the Completion of Inverse Entailment for Mutual Recursion and its Application to Self Recursion. In Proceedings of the Work-in-Progress Track, 10th International Conference on Inductive Logic Programming, Lecture Notes in Computer Science, 1866:107-119, Springer-Verlag, 2000.
3. K. Inoue. Induction, Abduction, and Consequence-Finding. In Proceedings 11th International Conference on Inductive Logic Programming, Lecture Notes in AI, 2157:65-79, Springer-Verlag, 2001.
4. A.C. Kakas, R.A. Kowalski, and F. Toni. Abductive Logic Programming. Journal of Logic and Computation, 2(6):719-770, 1992.
5. A.C. Kakas and P. Mancarella. Database Updates through Abduction. In Proceedings of the 16th International Conference on Very Large Databases, pages 650-661, Morgan Kaufmann, 1990.
6. A. Kakas, B. Van Nuffelen, and M. Denecker. A-system: Problem solving through abduction. In Proceedings of the 17th International Joint Conference on Artificial Intelligence, pages 591-596 Morgan Kaufmann, 2001.
7. S.H. Muggleton and C.H. Bryant. Theory Completion Using Inverse Entailment. In Proceedings of the 10th International Conference on Inductive Logic Programming, Lecture Notes in Computer Science, 1866:130-146, Springer-Verlag, 2000.
8. S.H. Muggleton and L. De Raedt. Inductive Logic Programming: Theory and Methods. Journal of Logic Programming, 19,20:629-679, 1994.
9. S.H. Muggleton. Inductive Logic Programming. New Generation Computing, 8(4):295-318, 1991.
10. S.H. Muggleton. Inverse Entailment and Progol. New Generation Computing, Special issue on Inductive Logic Programming, 13(3-4):245-286, 1995.
11. G.D. Plotkin. Automatic Methods of Inductive Inference. PhD thesis, Edinburgh University, 1971.
12. O. Ray. HAIL: Hybrid Abductive-Inductive Learning. Technical report 2003/6, Imperial College, Department of Computing, 2003.
13. M.E. Stickel. A Prolog technology theorem prover: Implementation by an extended Prolog compiler. Journal of Automated Reasoning, 4(4):353-380, 1988.
14. A. Yamamoto. Which Hypotheses Can Be Found with Inverse Entailment? In Proceedings of the 7th International Workshop on Inductive Logic Programming, Lecture Notes in Computer Science 1297:296-308, Springer-Verlag, 1997.
15. A. Yamamoto. An Inference Method for the Complete Inverse of Relative Subsumption. New Generation Computing, 17(1):99-117, 1999.
16. A. Yamamoto. Using Abduction for Induction based on Bottom Generalisation In Abduction and Induction: Essays on their relation and integration, Applied Logic Series 18:267-280, Kluwer Academic Publishers, 2000.
17. A. Yamamoto and B. Fronhöfer. Hypothesis Finding via Residue Hypotheses with the Resolution Principle. In Proceedings of the 11th International Conference on Algorithmic Learning Theory, Lecture Notes in Computer Science 1968:156-165, Springer-Verlag, 2000.