Modeling belief in dynamic systems Part II: revision and update

Journal of Artificial Intelligence Research

Volumn 10, Issue , 1999, Pages 117-167

  Friedman, Nir ^a   Halpern, Joseph Y ^b  

^a HEBREW UNIVERSITY OF JERUSALEM   (Israel)

^b Department of Computer Science and School of Operations Research and Information Engineering   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL METHODS; KNOWLEDGE BASED SYSTEMS; MATHEMATICAL MODELS; THEOREM PROVING;

BELIEF REVISION; BELIEF UPDATE; DYNAMIC SYSTEM;

ARTIFICIAL INTELLIGENCE;

EID: 0033307541     PISSN: 10769757     EISSN: None     Source Type: Journal    
DOI: 10.1613/jair.506     Document Type: Article

References (57)

1. Alchourrón, C. E., Gärdenfors, P., & Makinson, D. (1985). On the logic of theory change: partial meet functions for contraction and revision. Journal of Symbolic Logic, 50, 510-530.
2. Boutilier, C. (1992). Normative, subjective and autoepistemic defaults: adopting the Ramsey test. In Principles of Knowledge Representation and Reasoning: Proc. Third International Conference (KR '92), pp. 685-696. Morgan Kaufmann, San Francisco, Calif.
3. Boutilier, C. (1994a). Conditional logics of normality: a modal approach. Artificial Intelligence, 68, 87-154.
4. Boutilier, C. (1994b). Unifying default reasoning and belief revision in a modal framework. Artificial Intelligence, 68, 33-85.
5. Boutilier, C. (1996a). Iterated revision and minimal change of conditional beliefs. Journal of Philosophical Logic, 25, 262-305.
6. Boutilier, C. (1996b). Abduction to plausible causes: An event-based model of belief update. Artificial Intelligence, 83, 143-166.
7. Boutilier, C. (1998). A unified model of qualitative belief change: A dynamical systems perspective. Artificial Intelligence, 98, 281-316.
8. Boutilier, C., Friedman, N., & Halpern, J. Y. (1998). Belief revision with unreliable observations. In Proceedings, Fifteenth National Conference on Artificial Intelligence (AAAI '96), pp. 127-134.
9. Burgess, J. (1981). Quick completeness proofs for some logics of conditionals. Notre Dame Journal of Formal Logic, 22, 76-84.
10. Darwiche, A., & Pearl, J. (1997). On the logic of iterated belief revision. Artificial Intelligence, 89, 1-29.
11. Davis, R., & Hamscher, W. (1988). Model-based reasoning: troubleshooting. In Shrobe, H., & for Artificial Intelligence, T. A. A. (Eds.), Exploring AI, pp. 297-346. Morgan Kaufmann, SF.
12. de Rijke, M. (1992). Meeting some neighbors. Research report LP-92-10, University of Amsterdam.
13. del Val, A., & Shoham, Y. (1992). Deriving properties of belief update from theories of action. In Proceedings, Tenth National Conference on Artificial Intelligence (AAAI '92), pp. 584-589. AAAI Press, Menlo Park, CA.
14. del Val, A., & Shoham, Y. (1993). Deriving properties of belief update from theories of action (II). In Proc. Thirteenth International Joint Conference on Artificial Intelligence (IJCAI '93), pp. 732-737 San Francisco. Morgan Kaufmann.
15. del Val, A., & Shoham, Y. (1994). A unified view of belief revision and update. Journal of Logic and Computation, 4.
16. Dubois, D., & Prade, H. (1990). An introduction to possibilistic and fuzzy logics. In Shafer, G., & Pearl, J. (Eds.), Readings in Uncertain Reasoning, pp. 742-761. Morgan Kaufmann, San Francisco, Calif.
17. Dubois, D., & Prade, H. (1991). Possibilistic logic, preferential models, non-monotonicity and related issues. In Proc. Twelfth International Joint Conference on Artificial Intelligence (IJCAI '91), pp. 419-424. Morgan Kaufmann, San Francisco.
18. Fagin, R., Halpern, J. Y., Moses, Y., & Vardi, M. Y. (1995). Reasoning about Knowledge. MIT Press, Cambridge, Mass.
19. Freund, M., & Lehmann, D. (1994). Belief revision and rational inference. Tech. rep. TR 94-16, Hebrew University.
20. Friedman, N. (1997). Modeling Beliefs in Dynamic Systems. Ph.D. thesis, Stanford.
21. Friedman, N., & Halpern, J. Y. (1994). Conditional logics of belief change. In Proc. National Conference on Artificial Intelligence (AAAI '94), pp. 915-921. AAAI Press, Menlo Park, CA.
22. Friedman, N., & Halpern, J. Y. (1995). Plausibility measures: a user's manual. In Besnard, P., & Hanks, S. (Eds.), Proc. Eleventh Conference on Uncertainty in Artificial Intelligence (UAI '95), pp. 175-184. Morgan Kaufmann, San Francisco.
23. Friedman, N., & Halpern, J. Y. (1996). A qualitative Markov assumption and its implications for belief change. In Proc. Twelfth Conference on Uncertainty in Artificial Intelligence (UAI '96), pp. 263-273.
24. Friedman, N., & Halpern, J. Y. (1997). Modeling belief in dynamic systems. part I: foundations. Artificial Intelligence, 95(2), 257-316.
25. Friedman, N., & Halpern, J. Y. (1998a). Belief revision: A critique. Journal of Logic, Language and Information, To appear. Also available at http://www.cs.huji.ac. il/~nir. A preliminary version appeared in L. C. Aiello, J. Doyle, and S. C. Shapiro (eds.) Principles of Knowledge Representation and Reasoning: Proc. 5'th International Conference, pp. 421-431, 1996.
26. Friedman, N., & Halpern, J. Y. (1998b). Plausibility measures and default reasoning. Journal of the ACM, To appear. Also available at http://www.huji.ac.il/~nir. A preliminary version appeared in Proc., 13'th National Conference on Artificial Intelligence, pp. 1297-1304, 1996.
27. Fuhrmann, A. (1989). Reflective modalities and theory change. Synthese, 81, 115-134.
28. Gärdenfors, P. (1986). Belief revision and the Ramsey test for conditionals. Philosophical Review, 91, 81-93.
29. Gärdenfors, P. (1988). Knowledge in Flux. MIT Press, Cambridge, Mass.
30. Gärdenfors, P., & Makinson, D. (1988). Revisions of knowledge systems using epistemic entrenchment. In Proc. Second Conference on Theoretical Aspects of Reasoning about Knowledge, pp. 83-95. Morgan Kaufmann, San Francisco, Calif.
31. Goldszmidt, M., Morris, P., & Pearl, J. (1993). A maximum entropy approach to nonmonotonic reasoning. IEEE Transactions of Pattern Analysis and Machine Intelligence, 15(3), 220-232.
32. Goldszmidt, M., & Pearl, J. (1996). Qualitative probabilities for default reasoning, belief revision, and causal modeling. Artificial Intelligence, 84, 57-112.
33. Grahne, G., Mendelzon, A., & Rieter, R. (1992). On the semantics of belief revision systems. In Moses, Y. (Ed.), know92, pp. 132-142. Morgan Kaufmann, San Francisco, Calif.
34. Grove, A. (1988). Two modelings for theory change. Journal of Philosophical Logic, 17, 157-170.
35. Halpern, J. Y., & Fagin, R. (1989). Modelling knowledge and action in distributed systems. Distributed Computing, 3(4), 159-179. A preliminary version appeared in Proc. 4th ACM Symposium on Principles of Distributed Computing, 1985, with the title "A formal model of knowledge, action, and communication in distributed systems: preliminary report".
36. Halpern, J. Y., & Vardi, M. Y. (1989). The complexity of reasoning about knowledge and time, I: lower bounds. Journal of Computer and System Sciences, 38(1), 195-237.
37. Katsuno, H., & Mendelzon, A. (1991a). On the difference between updating a knowledge base and revising it. In Principles of Knowledge Representation and Reasoning: Proc. Second International Conference (KR '91), pp. 387-394. Morgan Kaufmann, San Francisco, Calif.
38. Katsuno, H., & Mendelzon, A. (1991b). Prepositional knowledge base revision and minimal change. Artificial Intelligence, 52(3), 263-294.
39. Katsuno, H., & Satoh, K. (1991). A unified view of consequence relation, belief revision and conditional logic. In Proc. Twelfth International Joint Conference on Artificial Intelligence (IJCAI '91), pp. 406-412.
40. Kautz, H. A. (1986). Logic of persistence. In Proceedings, Fifth National Conference on Artificial Intelligence (AAAI '86), pp. 401-405. AAAI Press, Menlo Park, CA.
41. Keller, A. M., & Winslett, M. (1985). On the use of an extended relational model to handle changing incomplete information. IEEE Transactions on Software Engineering, SE-11(7), 620-633.
42. Kraus, S., Lehmann, D., & Magidor, M. (1990). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence, 44, 167-207.
43. Lehmann, D. (1995). Belief revision, revised. In Proc. Fourteenth International Joint Conference on Artificial Intelligence (IJCAI '95), pp. 1534-1540. Morgan Kaufmann, San Francisco.
44. Levi, I. (1988). Iteration of conditionals and the Ramsey test. Synthese, 76, 49-81.
45. Lewis, D. K. (1973). Counterfactuals. Harvard University Press, Cambridge, Mass.
46. Manna, Z., & Pnueli, A. (1992). The Temporal Logic of Reactive and Concurrent Systems, Vol. 1. Springer-Verlag, Berlin/New York.
47. Nayak, A. C. (1994). Iterated belief change based on epistemic entrenchment. Erkenntnis, 41, 353-390.
48. Pearl, J. (1989). Probabilistic semantics for nonmonotonic reasoning: a survey. In Brachman, R. J., Levesque, H. J., & Reiter, R. (Eds.), Proc. First International Conference on Principles of Knowledge Representation and Reasoning (KR '89), pp. 505-516. Reprinted in Readings in Uncertain Reasoning, G. Shafer and J. Pearl (eds.), Morgan Kaufmann, San Francisco, Calif., 1990, pp. 699-710.
49. Rott, H. (1991). Two methods of constructing contractions and revisions of knowledge systems. Journal of Philosophical Logic, 20, 149-173.
50. Rott, H. (1992). Two methods of constructing contraction and revisions of knowledge systems. Journal of Logic, Language and Information, 1, 45-78.
51. Shafer, G. (1976). A Mathematical Theory of Evidence. Princeton University Press, Princeton, N.J.
52. Shoham, Y. (1987). A semantical approach to nonmonotonic logics. In Proc. 2nd IEEE Symp. on Logic in Computer Science, pp. 275-279. Reprinted in M. L. Ginsberg (Ed.), Readings in Nonmonotonic Reasoning, Morgan Kaufman, San Francisco, Calif., 1987, pp. 227-250.
53. Shoham, Y. (1988). Chronological ignorance: experiments in nonmonotonic temporal reasoning. Artificial Intelligence, 36, 271-331.
54. Spohn, W. (1988). Ordinal conditional functions: a dynamic theory of epistemic states. In Harper, W., & Skyrms, B. (Eds.), Causation in Decision, Belief Change, and Statistics, Vol. 2, pp. 105-134. Reidel, Dordrecht, Netherlands.
55. Wang, Z., & Klir, G. J. (1992). Fuzzy Measure Theory. Plenum Press, New York.
56. Williams, M. (1994). Transmutations of knowledge systems. In Principles of Knowledge Representation and Reasoning: Proc. Fourth International Conference (KR '94), pp. 619-629. Morgan Kaufmann, San Francisco, Calif.
57. Winslett, M. (1988). Reasoning about action using a possible models approach. In Proceedings, Seventh National Conference on Artificial Intelligence (AAAI '88), pp. 89-93. AAAI Press, Menlo Park, CA.