Propositional independence: Formula-variable independence and forgetting

Journal of Artificial Intelligence Research

Volumn 18, Issue , 2003, Pages 391-443

  Lang, Jérôme ^a   Liberatore, Paolo ^b   Marquis, Pierre ^c  

^a IRIT   (France)

^b SAPIENZA UNIVERSITY OF ROME   (Italy)

^c UNIVERSITÉ D'ARTOIS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; KNOWLEDGE ACQUISITION; QUERY LANGUAGES; SEMANTICS; SET THEORY; SYNTACTICS;

KNOWLEDGE BASES; PROPOSITIONAL INDEPENDENCE; REASONING TASKS; SUBSETS;

PROBLEM SOLVING;

EID: 14544275947     PISSN: 10769757     EISSN: 10769757     Source Type: Journal    
DOI: 10.1613/jair.1113     Document Type: Review

References (62)

1. Amir, E., & McIlraith, S. (2000). Partition-based logical reasoning. In Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR'00), pp. 389-400.
2. Biere, A., Cimatti, A., Clarke, E. M., Fujita, M., &: Zhu, Y. (1999). Symbolic model checking using SAT procedures instead of BDDs. In Proceedings of Design Automation Conference (DAC'99).
3. Boppana, R. B., & Sipser, M. (1990). The complexity of finite functions. In van Leeuwen, J. (Ed.), Handbook of Theoretical Computer Science, Vol. A, chap. 14. Elsevier Science Publishers (North-Holland), Amsterdam.
4. Boutilier, C. (1994). Toward a logic for qualitative decision theory. In Proceedings of the Fourth International Conference on the Principles of Knowledge Representation and Reasoning (KR'94), pp. 75-86.
5. Chopra, S., & Parikh, R. (1999). An inconsistency tolerant model for belief representation and belief revision. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI'99), pp. 192-197.
6. Darwiche, A. (1997). A logical notion of conditional independence: properties and applications. Artificial Intelligence, 57(1-2), 45-82.
7. Darwiche, A. (1998). Model-based diagnosis using structured system descriptions. Journal of Artificial Intelligence Research, 8, 165-222.
8. Darwiche, A. (1999). Compiling knowledge into decomposable negation normal form. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI'99), pp. 284-289.
9. Darwiche, A., & Marquis, P. (1999). A perspective on knowledge compilation. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI'01), pp. 175-182.
10. Davis, M., & Putnam, H. (1960). A computing procedure for quantification theory. Journal of the ACM, 7, 201-215.
11. Dechter, R., & Rish, I. (1994). Directional resolution; the davis-putnam procedure, revisited. In Proceedings of the Fourth International Conference on the Principles of Knowledge Representation and Reasoning (KR'94), PP. 134-145.
12. del Val, A. (1999). A new method for consequence finding and compilation in restricted language. In Proceedings of the Sixteenth National Conference on Artificial Intelligence (AAAI'99), pp. 259-264, Orlando (FL).
13. Doherty, P., Lukaszewicz, W., & Madalinska-Bugaj, E. (1998). The PMA and relativizing change for action update. In Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning (KR '98), pp. 258-269.
14. Doherty, P., Lukaszewicz, W., & Szalas, A. (2001). Computing strongest necessary and weakest sufficient conditions of first-order formulas. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI'01), pp. 145-151.
15. Fargier, H., Lang, J., & Marquis, P. (2000). Propositional logic and one-stage decision making. In Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR '00), pp. 445-456.
16. Fariñas del Cerro, L., & Herzig, A. (1996). Belief change and dependence. In Proceedings of the Sixth Conference on Theoretical Aspects of Reasoning about Knowledge (TARK'96), pp. 147-161.
17. Gelfond, M., & Lifschitz, V. (1993). Representing action and change by logic programs. Journal of Logic Programming, 17, 301-323.
18. Ghidini, C., & Giunchiglia, F. (2001). Local model semantics, or contextual reasoning = locality + compatibility. Artificial Intelligence, 127, 221-259.
19. Goldblatt, R. (1987). Logics of Time and Computation, Vol. 7 of CSLI Lecture Notes. Center for the Study of Language and Information, Stanford, CA.
20. Greiner, R., & Genesereth, M. R. (1983). What's new? a semantic definition of novelty. In Proceedings of the Eighth International Joint Conference on Artificial Intelligence (IJCAI'83), pp. 450-454.
21. Greiner, R., & Subramanian, D. (1995). Proceedings of the AAAI fall symposium on relevance.. Technical Report FS-94-02, AAAI Press.
22. Hegner, S. (1987). Specification and implementation of programs for updating incomplete information databases. In Proceedings of the Sixth ACM SIGACT SIGMOD SIGART Symposium on Principles of Database Systems (PODS'87), pp. 146-158.
23. Herzig, A. (1996). The PMA revisited. In Proceedings of the Fifth International Conference on the Principles of Knowledge Representation and Reasoning (KR'96), pp. 40-50.
24. Herzig, A., Lang, J., Marquis, P., & Polacsek, T. (2001). Updates, actions, and planning. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI'01), pp. 119-124.
25. Herzig, A., & Rifi, O. (1998). Update operations: a review. In Proceedings of the Thirteenth European Conference on Artificial Intelligence (ECAI'98), pp. 13-17.
26. Herzig, A., & Rifi, O. (1999). Propositional belief base update and minimal change. Artificial Intelligence, 115(1), 107-138.
27. Inoue, K. (1992). Linear resolution in consequence-finding. Artificial Intelligence, 50(2-3), 301-353.
28. Kautz, H., Kearns, M., & Selman, B. (1993). Reasoning with characteristic models. In Proceedings of the Eleventh National Conference on Artificial Intelligence (AAAI'93), pp. 34-39.
29. Kautz, H., Kearns, M., & Selman, B. (1995). Horn approximations of empirical data. Artificial Intelligence, 74(1), 129-145.
30. Kautz, H., McAllester, D., & Selman, B. (1996). Encoding plans in prepositional logic. In Proceedings of the Fifth International Conference on the Principles of Knowledge Representation and Reasoning (KR'96), pp. 374-384.
31. Khardon, R., & Roth, D. (1996). Reasoning with models. Artificial Intelligence, 87(1-2), 187-213.
32. Kohlas, J., Moral, S., & Haenni, R. (1999). Propositional information systems. Journal of Logic and Computation, 9(5), 651-681.
33. Lakemeyer, G. (1995). A logical account of relevance. In Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence (IJCAI'95), pp. 853-859.
34. Lakemeyer, G. (1997). Relevance from an epistemic perspective. Artificial Intelligence, 97(1-2), 137-167.
35. Lang, J., Liberatore, P., & Marquis, P. (2002). Conditional independence in propositional logic. Artificial Intelligence, 141(1-2), 79-121.
36. Lang, J., & Marquis, P. (1998a). Complexity results for independence and definability in propositional logic. In Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning (KR'98), pp. 356-367.
37. Lang, J., & Marquis, P. (1998b). Two notions of dependence in propositional logic: controllability and definability. In Proceedings of the Fifteenth National Conference on Artificial Intelligence (AAAI'98), pp. 268-273.
38. Lang, J., & Marquis, P. (2002). Resolving inconsistencies by variable forgetting. In Proceedings of the Eighth International Conference on Principles of Knowledge Representation and Reasoning (KR'02), pp. 239-250.
39. Lang, J., Marquis, P., & Williams, M.-A. (2001). Updating epistemic states. In Proceedings of the Fourteenth Australian Joint Conference on Artificial Intelligence (AI'01), pp. 297-308.
40. Levy, A., Fikes, R., & Sagiv, Y. (1997). Speeding up inferences using relevance reasoning: A formalism and algorithms. Artificial Intelligence, 57(1-2), 83-136.
41. Lin, F. (2000). On strongest necessary and weakest sufficient conditions. In Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR'00), pp. 167-175.
42. Lin, F., & Reiter, R. (1994). Forget it!. In Proceedings of the AAAI Fall Symposium on Relevance, pp. 154-159.
43. Marquis, P. (1994). Possible models approach via independency. In Proceedings of the Eleventh European Conference on Artificial Intelligence (ECAI'94), pp. 336-340.
44. Marquis, P. (2000). Consequence finding algorithms. In Handbook on Defeasible Reasoning and Uncertainty Management Systems, Volume 5: Algorithms for Uncertain and Defeasible Reasoning, chap. 2, pp. 41-145. Kluwer Academic Publishers.
45. Marquis, P., & Porquet, N. (2000). Decomposing propositional knowledge bases through topics (extended abstract). In Proceedings of the meeting on "Partial knowledge and uncertainty: independence, conditioning, inference".
46. McCarthy, J. (1986). Applications of circumscription to formalizing common-sense knowledge. Artificial Intelligence, 28, 89-116.
47. McIlraith, S., & Amir, E. (2001). Theorem proving with structured theories. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI'01), pp. 624-631.
48. Papadimitriou, C. H. (1994). Computational Complexity. Addison-Wesley.
49. Parikh, R. (1996). Beliefs, belief revision, and splitting languages, pp. 266-268. Logic, Language and Computation. CSLI Publications.
50. Park, T. J., & Gelder, A. V. (1996). Partitioning methods for satisfiability testing on large formulas. In Proceedings of the Thirteenth International Conference on Automated Deduction (CADE'96), pp. 748-762.
51. Przymusinski, T. C. (1989). An algorithm to compute circumscription. Artificial Intelligence, 88, 49-73.
52. Reiter, R. (1987). A theory of diagnosis from first principles. Artificial Intelligence, 32, 57-95.
53. Rintanen, J. (2001). Partial implicit unfolding in the Davis-Putnam procedure for quantified boolean formulae. In Proceedings of the QBF2001 Workshop at IJCAR'01, pp. 84-93.
54. Ryan, M. D. (1991). Defaults and revision in structured theories. In Proceedings of the Sixth IEEE Symposium on Logic in Computer Science (LICS'91), pp. 362-373.
55. Ryan, M. D. (1992). Ordered presentations of theories. Ph.D. thesis, Imperial College, London.
56. Sandewall, E. (1995). Features and Fluents. Oxfor University Press.
57. Siegel, P. (1987). Représentation et utilisation des connaissances en calcul propositionnel. Thèse d'État, Université d'Aix-Marseille 2. (in french).
58. Simon, L., & del Val, A. (2001). Efficient consequence finding. In Proceedings of the Seventeenth International Joint Conference on Artificial Intelligence (IJCAI'01), pp. 359-365.
59. Subramanian, D., Greiner, R., & Pearl, J. (1997). Artificial Intelligence Journal: Special Issue on Relevance, 97 (1-2), 1997.
60. Tan, S., & Pearl, J. (1994). Specification and evaluation of preferences for planning under uncertainty. In Proceedings of the Fourth International Conference on the Principles of Knowledge Representation and Reasoning (KR '94).
61. Williams, P. F., Biere, A., Clarke, E. M., & Gupta, A. (2000). Combining Decision Diagrams and SAT Procedures for Efficient Symbolic Model Checking. In Proceedings of the Twelfth International Conference on Computer Aided Verification (CAV'00).
62. Winslett, M. (1990). Updating Logical Databases. Cambridge Tracts in Theoretical Computer Science. Cambridge University Press.