A causal theory of abduction

7th International Symposium on Logical Formalizations of Commonsense Reasoning, Commonsense 2005

Volumn , Issue , 2005, Pages

  Bochman, Alexander ^a  

^a HOLON INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

ABDUCTIVE LOGIC PROGRAMMING; ABDUCTIVE REASONING; CAUSAL INFERENCES; CAUSAL THEORY; LOGICAL FRAMEWORKS;

LOGIC PROGRAMMING;

EID: 84888358435     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. A. Bochman. A logic for causal reasoning. In Proceedings IJCAI'03, Acapulco, 2003. Morgan Kaufmann.
2. A. Bochman. A causal approach to nonmonotonic reasoning. Artificial Intelligence, 160:105-143, 2004.
3. A. Bochman. A causal logic of logic programming. In D. Dubois, C. Welty, and M.-A. Williams, editors, Proc. Ninth Conference on Principles of Knowledge Representation and Reasoning, KR'04, pages 427-437, Whistler, 2004.
4. L. Console, D. Theseider Dupre, and P. Torasso. On the relationship between abduction and deduction. Journal of Logic and Computation, 1:661-690, 1991.
5. P. T. Cox and T. Pietr zykowski. General diagnosis by abductive inference. In Proc. IEEE Symposium on Logic Programming, pages 183-189, 1987.
6. A. Darwiche and J. Pearl. Symbolic causal networks. In Proceedings AAAI'94, pages 238-244, 1994.
7. J. De Kleer, A. K. Mackworth, and R. Reiter. Characterizing diagnoses and systems. Artificial Intelligence, 52:197-222, 1992.
8. E. Giunchiglia, J. Lee, V. Lifschitz, N. McCain, and H. Turner. Nonmonotonic causal theories. Artificial Intelligence, 153:49-104, 2004.
9. K. Inoue and C. Sakama. Negation as failure in the head. Journal of Logic Programming, 35:39-78, 1998.
10. A. C. Kakas and P. Mancar ella. Generalized stable models: A semantics for abduction. In Proc. European Conf. on Artificial Intelligence, ECAI-90, pages 385-391, Stockholm, 1990.
11. A. C. Kakas, R. A. Kowalski, and F. Toni. The ro le of abduction in logic programming. In D. M. Gabbay, C. J. Hogger, and R. A. Robinson, editors, Handbook of Logic in Artificial Intelligence and Logic Programming, volume 5, pages 235-324. Oxford UP, 1998.
12. K. Konolige. Abduction versus closure in causal theories. Artificial Intelligence, 53:255-272, 1992.
13. K. Konolige. Using default and causal reasoning in diagnosis. Annals of Mathematics and Artificial Intelligence, 11:97-135, 1994.
14. J. Lobo and C. Uzćategui. Abductive consequence relations. Artificial Intelligence, 89:149-171, 1997.
15. N. McCain and H. Turner. Causal theories of action and change. In Proceedings AAAI-97, pages 460-465, 1997.
16. J. Pearl. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, 1988.
17. D. Poole. A logical framework for default reasoning. Artificial Intelligence, 36:27-47, 1988.
18. D. Poole. Representing knowledge for logicbased diagnosis. In Proc. Int. Conf. on Fifth Generation Computer Systems, pages 1282-1290, Tokyo, 1988.
19. D. Poole. Representing diagnosis knowledge. Annals of Mathematics and Artificial Intelligence, 11:33-50, 1994.
20. D. Poole. Abducing through negation as failure: Stable models within the independent choice logic. Journal of Logic Programming, 44:5-35, 2000.
21. R. Reiter. A theory of diagnosis from first principles. Artificial Intelligence, 32:57-95, 1987.