Skip to main content
Log in

How to Revise a Total Preorder

  • Published:
Journal of Philosophical Logic Aims and scope Submit manuscript

Abstract

Most approaches to iterated belief revision are accompanied by some motivation for the use of the proposed revision operator (or family of operators), and typically encode enough information in the epistemic state of an agent for uniquely determining one-step revision. But in those approaches describing a family of operators there is usually little indication of how to proceed uniquely after the first revision step. In this paper we contribute towards addressing that deficiency by providing a formal framework which goes beyond the first revision step in two ways. First, the framework is obtained by enriching the epistemic state of an agent starting from the following intuitive idea: we associate to each world x two abstract objects x + and x , and we assume that, in addition to preferences over the set of worlds, we are given preferences over this set of objects as well. The latter can be considered as meta-information encoded in the epistemic state which enables us to go beyond the first revision step of the revision operator being applied, and to obtain a unique set of preferences over worlds. We then extend this framework to consider, not only the revision of preferences over worlds, but also the revision of this extended structure itself. We look at some desirable properties for revising the structure and prove the consistency of these properties by giving a concrete operator satisfying all of them. Perhaps more importantly, we show that this framework has strong connections with two other types of constructions in related areas. Firstly, it can be seen as a special case of preference aggregation which opens up the possibility of extending the framework presented here into a full-fledged framework for preference aggregation and social choice theory. Secondly, it is related to existing work on the use of interval orderings in a number of different contexts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Alchourrón, C., Gärdenfors, P., & Makinson, D. (1985). On the logic of theory change: Partial meet contraction and revision functions. Journal of Symbolic Logic, 50(2), 510–530.

    Article  Google Scholar 

  2. Allen, J. F. (1983). Maintaining knowledge about temporal intervals. Communications of the ACM, 26(11), 832–843.

    Article  Google Scholar 

  3. Arrow, K. (1963). Social choice and individual values. New York: Wiley.

    Google Scholar 

  4. Benferhat, S., Konieczny, S., Papini, O., & Pérez, R. P. (2000). Iterated revision by epistemic states: Axioms, semantics and syntax. In ECAI (pp. 13–17).

  5. Bochman, A. (2001). A logical theory of nonmonotonic inference and belief change. Berlin: Springer.

  6. Booth, R. (2005). On the logic of iterated non-prioritised revision. In Conditionals, information and inference—Selected papers from the workshop on conditionals, information and inference, 2002 (pp. 86–107). LNAI 3301. New York: Springer.

    Google Scholar 

  7. Booth, R., & Meyer, T. (2006). Admissible and restrained revision. Journal of Artificial Intelligence Research (JAIR), 26, 127–151.

    Google Scholar 

  8. Booth, R., Meyer, T., & Wong, K. S. (2006). A bad day surfing is better than a good day working: How to revise a total preorder. In KR (pp. 230–238). AAAI Press.

  9. Booth, R., Chopra, S., Ghose, A., & Meyer, T. (2010). Double preference relations for generalised belief change. Artificial Intelligence, 174(16–17), 1339–1368.

    Article  Google Scholar 

  10. Booth, R., & Meyer, T. A. (2007). On the dynamics of total preorders: Revising abstract interval orders. In ECSQARU (pp. 42–53).

  11. Boutilier, C. (1996). Iterated revision and minimal change of conditional beliefs. Journal of Philosophical Logic, 25(3), 263–305.

    Article  Google Scholar 

  12. Darwiche, A., & Pearl, J. (1997). On the logic of iterated belief revision. Artificial Intelligence, 89, 1–29.

    Article  Google Scholar 

  13. Delgrande, J., Dubois, D., & Lang, J. (2006). Iterated revision as prioritized merging. In KR (pp. 210–220).

    Google Scholar 

  14. Dubois, D., Lang, J., & Prade, H. (1994). Possibilistic logic. Clarendon.

  15. Fishburn, P. C. (1985). Interval orders and interval graphs. New York: Wiley.

    Google Scholar 

  16. Freund, M. (1993). Injective models and disjunctive relations. Journal of Logic and Computation, 3(3), 231.

    Article  Google Scholar 

  17. Freund, M., & Lehmann, D. (1994). Belief revision and rational inference. Technical Report TR 94-16, The Leibniz Centre for Research in Computer Science, Institute of Computer Science, Hebrew University of Jerusalem.

  18. Geffner, H., & Pearl, J. (1992). Conditional entailment: Bridging two approaches to default entailment. Artificial Intelligence, 53, 209–244.

    Article  Google Scholar 

  19. Glaister, S. M. (1998). Symmetry and belief revision. Erkenntnis, 49(1), 21–56.

    Article  Google Scholar 

  20. Grove, A. (1988). Two modelings for theory change. Journal of Philosophical Logic, 17, 157–170.

    Article  Google Scholar 

  21. Hansson, S. O., Fermé, E., Cantwell, J., & Falappa, M. (2001). Credibility-limited revision. Journal of Symbolic Logic, 66(4), 1581–1596.

    Article  Google Scholar 

  22. Hansson, S. O. (1999). A survey of non-prioritized belief revision. Erkenntnis, 50(2), 413–427.

    Article  Google Scholar 

  23. Jin, Y., & Thielscher, M. (2007). Iterated belief revision, revised. Artificial Intelligence, 171(1), 1–18.

    Article  Google Scholar 

  24. Katsuno, H., & Mendelzon, A. O. (1991). Propositional knowledge base revision and minimal change. Artificial Intelligence, 52(3), 263–294.

    Article  Google Scholar 

  25. Konieczny, S., Medina Grespan, M., & Pino Pérez, R. (2010). Taxonomy of improvement operators and the problem of minimal change. In KR.

  26. Konieczny, S., & Pérez, R. P. (2000). A framework for iterated revision. Journal of Applied Non-Classical Logics, 10(3–4), 339–367.

    Google Scholar 

  27. Konieczny, S., & Pérez, R. P. (2008). Improvement operators. In KR (pp. 177–186).

  28. Kraus, S., Lehmann, D., & Magidor, M. (1991). Nonmonotonic reasoning, preferential models and cumulative logics. Artificial Intelligence, 44, 167–207.

    Article  Google Scholar 

  29. Lehmann, D. (1995). Belief revision, revised. In IJCAI (pp. 1534–1540).

  30. Nayak, A., Pagnucco, M., & Peppas, P. (2003). Dynamic belief revision operators. Artificial Intelligence, 146, 193–228.

    Article  Google Scholar 

  31. Nayak, A. C. (1994). Iterated belief change based on epistemic entrenchment. Erkenntnis, 41(3), 353–390.

    Article  Google Scholar 

  32. Öztürk, M., Tsoukiàs, A., & Vincke, P. (2005). Preference modelling. In Multiple criteria decision analysis: State of the art surveys (Vol. 78, pp. 27–71). New York: Springer.

    Google Scholar 

  33. Papini, O. (2001). Iterated revision operations stemming from the history of an agent’s observations. In Frontiers of belief revision (pp. 279–301).

  34. Rott, H. (2001). Change, choice and inference: A study of belief revision and nonmonotonic reasoning. London, UK: Oxford University Press.

    Google Scholar 

  35. Schlechta, K., Lehmann, D., & Magidor, M. (1996). Distance semantics for belief revision. In TARK (pp. 137–145).

  36. Spohn, W. (1988). Ordinal conditional functions: A dynamic theory of epistemic states. Causation in Decision, Belief Change, and Statistics, 2, 105–134.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Richard Booth.

Additional information

This paper is a combined and extended version of papers which first appeared in the proceedings of KR 2006, the 10th International Conference on Principles of Knowledge Representation and Reasoning [8], and ECSQARU 2007, the 9th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty [10].

Rights and permissions

Reprints and permissions

About this article

Cite this article

Booth, R., Meyer, T. How to Revise a Total Preorder. J Philos Logic 40, 193–238 (2011). https://doi.org/10.1007/s10992-011-9172-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10992-011-9172-8

Keywords

Navigation