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Epistemic Logics for Information Fusion

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2711))

Abstract

In this paper, we propose some extensions of epistemic logic for reasoning about information fusion. The fusion operators considered in this paper include majority merging, arbitration, and general merging. Some modalities corresponding to these fusion operators are added to epistemic logics and the Kripke semantics of these extended logics are presented. While most existing approaches treat information fusion operators as meta-level constructs, these operators are directly incorporated into our object logic language. Thus it is possible to reason about not only the merged results but also the fusion process in our logics.

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References

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

    Article  MATH  MathSciNet  Google Scholar 

  2. Arlo-Costa, H.L., Shapiro, S.J.: Maps between nonmonotonic and conditional logic. In: Nebel, B., Rich, C., Swartout, W. (eds.) Proceedings of the 3rd International Conference on Principle of Knowledge Representation and Reasoning, pp. 553–564. Morgan Kaufmann, San Francisco (1992)

    Google Scholar 

  3. Benferhat, S., Dubois, D., Prade, H.: From semantic to syntactic approaches to information combination in possibilistic logic. In: Bouchon-Meunier, B. (ed.) Aggregation and Fusion of Imperfect Information, pp. 141–161. Physica-Verlag, Heidelberg (1997)

    Google Scholar 

  4. Boldrin, L., Saffiotti, A.: A modal logic for merging partial belief of multiple reasoners. Journal of Logic and Computation 9(1), 81–103 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  5. Boldrin, L., Sossai, C.: An algebraic semantics for possibilistic logic. In: Proceedings of the 11th International Conference on Uncertainty in Artificial Intelligence, pp. 24–37 (1995)

    Google Scholar 

  6. Boldrin, L., Sossai, C.: Partial information and necessity-valued logic. In: Proceedings of the 6th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, pp. 941–946 (1996)

    Google Scholar 

  7. Boldrin, L., Sossai, C.: Local possibilistic logic. Journal of Applied Non-Classical Logic 7(3), 309–333 (1997)

    MATH  MathSciNet  Google Scholar 

  8. Boutilier, C.: Revision sequences and nested conditionals. In: Proceedings of the 13th International Joint Conference on Artificial Intelligence, pp. 519–525 (1993)

    Google Scholar 

  9. Boutilier, C.: Conditional logics of normality: a modal approach. Artificial Intelligence 68, 87–154 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  10. Boutilier, C.: Toward a logic for qualitative decision theory. In: Proceedings of the Fourth International Conference on Principles of Knowledge Representation and Reasoning, pp. 75–86 (1994)

    Google Scholar 

  11. Boutilier, C.: Generalized update: Belief change in dynamic settings. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 1550–1556 (1995)

    Google Scholar 

  12. Cholvy, L.: A logiccal approach to multi-souces reasoning. In: Masuch, M., Pólos, L. (eds.) Logic at Work 1992. LNCS, vol. 808, pp. 183–196. Springer, Heidelberg (1994)

    Google Scholar 

  13. Cholvy, L., Garion, C.: A logic to reason with contradictory beliefs with a majority approach. In: Proceedings of the IJCAI Workshop on Inconsistency in Data and Knowledge (2001)

    Google Scholar 

  14. Cholvy, L., Garion, C.: Answering queries addressed to several databases: a query evaluator which implements a majority merging approach. In: Hacid, M.-S., Raś, Z.W., Zighed, D.A., Kodratoff, Y. (eds.) ISMIS 2002. LNCS (LNAI), vol. 2366, pp. 131–139. Springer, Heidelberg (2002)

    Chapter  Google Scholar 

  15. Cholvy, L., Hunter, A.: Information fusion in logic: A brief overview. In: Nonnengart, A., Kruse, R., Ohlbach, H.J., Gabbay, D.M. (eds.) FAPR 1997 and ECSQARU 1997. LNCS (LNAI), vol. 1244, pp. 86–95. Springer, Heidelberg (1997)

    Chapter  Google Scholar 

  16. Dalal, M.: Investigations into a theory of knowledge base revision: Preliminary report. In: Proceedings of the 7th National Conference on Artificial Intelligence, pp. 475–479. AAAI Press, Menlo Park (1988)

    Google Scholar 

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

    Article  MATH  MathSciNet  Google Scholar 

  18. Dubois, D., Prade, H.: Belief change and possibility theory. In: Gärdenfors, P. (ed.) Belief Revision, pp. 142–182. Cambridge University Press, Cambridge (1992)

    Chapter  Google Scholar 

  19. Dubois, D., Prade, H.: Possibility theory in information fusion. In: Proc. of the Third International Conference on Information Fusion, p. TuA–1 (2000)

    Google Scholar 

  20. Fagin, R., Halpern, J.Y., Moses, Y., Vardi, M.Y.: Reasoning about Knowledge. MIT Press, Cambridge (1996)

    Google Scholar 

  21. Hintikka, J.: Knowledge and Belief. Cornell University Press (1962)

    Google Scholar 

  22. Maynard-Reid II, P., Shoham, Y.: Belief fusion: Aggregating pedigreed belief states. Journal of Logic, Language and Information 10(2), 183–209 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  23. Katsuno, H., Medelzon, A.: On the difference between updating a knowledge base and revising it. In: Proceedings of the Second International Conference on Principles of Knowledge Representation and Reasoning (KR 1991), pp. 387–394. Morgan Kaufmann Publisher, San Francisco (1991)

    Google Scholar 

  24. Katsuno, H., Medelzon, A.: Propositional knowledge base revision and minimal change. Artificial Intelligence 52, 263–294 (1991)

    Article  MATH  MathSciNet  Google Scholar 

  25. Konieczny, S.: On the difference between merging knowledge bases and combining them. In: Proceedings of the Seventh International Conference on Principles of Knowledge Representation and Reasoning (KR 2000), pp. 135–144. Morgan Kaufmann Publisher, San Francisco (2000)

    Google Scholar 

  26. Konieczny, S., Pino Pérez, R.: On the logic of merging. In: Proceedings of the Sixth International Conference on Principles of Knowledge Representation and Reasoning (KR 1998), pp. 488–498. Morgan Kaufmann Publisher, San Francisco (1998)

    Google Scholar 

  27. Konieczny, S., Pino Pérez, R.: Merging with integrity constraints. In: Hunter, A., Parsons, S. (eds.) ECSQARU 1999. LNCS (LNAI), vol. 1638, pp. 233–244. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  28. Lehmann, D.: Belief revision, revised. In: Proceedings of the 14th International Joint Conference on Artificial Intelligence, pp. 1534–1540 (1995)

    Google Scholar 

  29. Liau, C.J., Lin, I.P.: Quantitative modal logic and possibilistic reasoning. In: Neumann, B. (ed.) Proceedings of the 10th ECAI, pp. 43–47. John Wiley & Sons. Ltd, Chichester (1992)

    Google Scholar 

  30. Liau, C.J., Lin, I.P.: Proof methods for reasoning about possibility and necessity. International Journal of Approximate Reasoning 9(4), 327–364 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  31. Liau, C.J., Lin, I.P.: Possibilistic Reasoning—A Mini-survey and Uniform Semantics. Artificial Intelligence 88, 163–193 (1996)

    Article  MATH  MathSciNet  Google Scholar 

  32. Liberatore, P., Schaerf, M.: Arbitration: A commutative operator for belief revision. In: Proceedings of the Second World Conference on the Fundamentals of Artificial Intelligence (WOCFAI 1995), pp. 217–228 (1995)

    Google Scholar 

  33. Lin, J.: Information sharing and knowledge merging in cooperative information systems. In: Proceedings of the Fourth Workshop on Information Technologies and Systems, pp. 58–66 (1994)

    Google Scholar 

  34. Lin, J.: Integration of weighted knowledge bases. Artificial Intelligence 83(2), 363–378 (1996)

    Article  MathSciNet  Google Scholar 

  35. Lin, J., Mendelzon, A.O.: Knowledge base merging by majority. In: Pareschi, R., Fronhoefer, B. (eds.) Dynamic Worlds: From the Frame Problem to Knowledge Management. Kluwer Academic Publisher, Dordrecht (1999)

    Google Scholar 

  36. Meyer, J.-J.C., van der Hoek, W.: Epistemic Logic for AI and Computer Science. Cambridge University Press, Cambridge (1995)

    Book  MATH  Google Scholar 

  37. Nute, D.: Conditional logic. In: Gabbay, D.M., Guenthner, F. (eds.) Handbook of Philosophical Logic, Vol II: Extensions of Classical Logic, pp. 387–439. Reidel Publishing Company, Dordrechtz (1984)

    Google Scholar 

  38. Revesz, P.Z.: On the semantics of theory change: Arbitration between old and new information. In: Proceedings of the Twelfth ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, pp. 71–82 (1993)

    Google Scholar 

  39. Revesz, P.Z.: On the semantics of arbitration. International Journal of Algebra and Computation 7(2), 133–160 (1997)

    Article  MathSciNet  Google Scholar 

  40. Schlechta, K., Makinson, D.: Local and global metrics for the semantics of counterfactual conditionals. Journal of Applied Non-Classical Logics 4(2), 129–140 (1994)

    MATH  MathSciNet  Google Scholar 

  41. Segerberg, K.: Belief revision from the point of view of doxastic logic. Bull. of the IGPL 3(4), 535–553 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  42. Smets, P.: Data fusion in the transferable belief model. In: Proc. of the Third International Conference on Information Fusion, p–1 (2000)

    Google Scholar 

  43. Spohn, W.: Ordinal conditional functions: a dynamic theory of epistemic states. In: Harper, W.L., Skyrms, B. (eds.) Causation in Decision, Belief Change, and Statistics, II, pp. 105–134. Kluwer Academic Publishers, Dordrecht (1988)

    Google Scholar 

  44. Williams, M.A.: Transmutations of knowledge systems. In: Doyle, J., Sandewall, E., Torasso, P. (eds.) Proceedings of the 4th International Conference on Principle of Knowledge Representation and Reasoning, pp. 619–629. Morgan Kaufmann Publishers, San Francisco (1994)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Academia Sinica, Institute of Information Science, Taipei, 115, Taiwan

    Churn-Jung Liau

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  1. Churn-Jung Liau
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Editors and Affiliations

  1. Department of Computer Science, Aalborg University, Fredrik Bajersvej 7E, 9220, Aalborg, Denmark

    Thomas Dyhre Nielsen

  2. Department of Computer Science, Hong Kong University of Science and Technology, ClearWater Bay Road, Kowloon, Hong Kong, China,

    Nevin Lianwen Zhang

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Liau, CJ. (2003). Epistemic Logics for Information Fusion. In: Nielsen, T.D., Zhang, N.L. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2003. Lecture Notes in Computer Science(), vol 2711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45062-7_40

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  • DOI: https://doi.org/10.1007/978-3-540-45062-7_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40494-1

  • Online ISBN: 978-3-540-45062-7

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