Bipolar version space learning

International Journal of Intelligent Systems

Volumn 23, Issue 10, 2008, Pages 1135-1152

  Prade, Henri ^a   Serrurier, Mathieu ^a  

^a UNIVERSITÉ PAUL SABATIER   (France)

Author keywords

[No Author keywords available]

Indexed keywords

INFORMATION PROCESSING; POSSIBILITY THEORIES; VERSION SPACES;

EID: 55349092680     PISSN: 08848173     EISSN: 1098111X     Source Type: Journal    
DOI: 10.1002/int.20310     Document Type: Article

References (15)

1. Mitchell T. Generalization as search. Artificial intelligence 1982;18:203-226.
2. Hüllermeier E. Inducing fuzzy concepts through extended version space learning. In: Proc of 10th Int. Fuzzy Systems Association (IFSA-03); 2003. pp 677-684.
3. Nienhuys-Cheng S-H, de Wolf R. Foundations of Inductive Logic Programming. Number 1228 in LNAI. Springer; 1997.
4. Quinlan JR. Learning logical definitions from relations. Machine Learning 1990;5:239-266.
5. Muggleton SH. Inverse entailment and Progol. New Generation Computing 1995;13:245-286.
6. Dubois D, Prade H, Smets P. Not impossible vs. guaranted possible in fusion and revision. In: Proc of the 6th. European Conference (ESCQARU 2001), Toulouse, France, Springer-Verlag, 19-21 September 2001. pp 522-531. BB.
7. Zadeh LA. Fuzzy sets as abasis for a theory of possibility. Fuzzy sets and systems 1978;1:3-25.
8. Dubois D, Lang J, Prade H. Possibilistic logic. In: Gabbay D, et al., editor, Handbook of Logic in Artificial Intelligence and Logic Programming, vol 3, Oxford University Press, 1994. pp 439-513.
9. Dubois D, Prade H. Possibility theory as a basis for preference propagation in automated reasoning. In: Proc of the 1st IEEE Inter. Conf. on Fuzzy Systems (FUZZ-IEEE'92), 1992. pp 821-832.
10. Gärdenfors P. Knowledge in Flux. The MIT Press; 1988.
11. Dubois D, Prade H. Possibility theory: qualitative and quantitative aspects. In: Dov M. Gabbay, Philippe Smets, editors. Quantified Representation of Uncertainty and Imprecision, vol 1, Handbook of Defeasible Reasoning and Uncertainty Management Systems, The Netherlands: Kluwer academic publishers, 1998; BB. pp 169-226.
12. Serrurier M, Prade H. Coping with exceptions in multiclass ILP problems using possilistic logic. In: Proc of the 19th International Joint Conference on Artificial Intelligence (IJCAI-05), 2005. pp 1761-1764.
13. Sebag M. Using constraints to build version spaces. In: Bergadano F, De Raedt L. editors. Proceedings of the 7th European Conference on Machine Learning, vol 784. Lecture Notes in Artificial Intelligence Springer-Verlag, 1994. pp 257-271.
14. Hirsh H. Polynomial-time learning with version spaces. In: National Conference on Artificial Intelligence, 1992. pp 117-122.
15. Serrurier M, Prade H. Possibilistic inductive logic programming. In: Godo L, editor. Proceedings of European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU'05)-LNAI 3571, Barcelone, Berlin Heidelberg; Springer-Verlag, 2005. pp 675-686.