Reasoning in Epistemic Contexts

  • Yves BouchardEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10257)


In this paper, I develop a framework for representing knowledge, that aims at exploiting logically epistemological objects, namely epistemic contexts. Even though this framework is mostly logical and epistemological in character, it takes advantage of many works in artificial intelligence, in particular the ones of McCarthy and Buvač (1997). In Sect. 1, I characterize the notion of epistemic contexts. In Sect. 2, I present a natural deduction system that allows for the introduction and the elimination of knowledge operators. Such a system enables classical reasoning among contexts governed by different concepts of knowledge. Finally, in Sect. 3, I discuss some corollaries of the proposed framework (knowledge transfer, introspection, and closure).


Natural Deduction Epistemic Normativity Epistemic Agent Epistemic Standard Closure Principle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Baader, F., McGuinness, D.L., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation, and Applications. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  2. 2.
    Barwise, J.: The Situation in Logic. CSLI, Stanford (1989)zbMATHGoogle Scholar
  3. 3.
    van Benthem, J.: Changing contexts and shifting assertions. In: Aliseda, A., van Glabbeek, R., Westerståhl, D. (eds.) Computing Natural Language, pp. 51–65. CSLI Publications, Stanford (1998)Google Scholar
  4. 4.
    van Benthem, J.: McCarthy variations in a modal key. Artif. Intell. 175, 428–439 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  5. 5.
    Bouchard, Y.: Epistemic contexts and indexicality. In: Lihoreau, F., Rebuschi, M. (eds.) Epistemology, Context, and Formalism, Synthese Library, vol. 369, pp. 59–79. Springer International Publishing, Cham (2014)CrossRefGoogle Scholar
  6. 6.
    Bouquet, P., Ghidini, C., Giunchiglia, F., Blanzieri, E.: Theories and uses of context in knowledge representation and reasoning. J. Pragmat. 35, 455–484 (2003)CrossRefGoogle Scholar
  7. 7.
    Bouquet, P., Serafini, L.: Two formalizations of context: a comparison. In: Akman, V., Bouquet, P., Thomason, R., Young, R. (eds.) CONTEXT 2001. LNCS (LNAI), vol. 2116, pp. 87–101. Springer, Heidelberg (2001). doi: 10.1007/3-540-44607-9_7 CrossRefGoogle Scholar
  8. 8.
    Brézillon, P.: Context in problem solving: a survey. Knowl. Eng. Rev. 14, 47–80 (1999)CrossRefzbMATHGoogle Scholar
  9. 9.
    Buvač, S.: Resolving lexical ambiguity using a formal theory of context. In: van Deemter, K., Peters, S. (eds.) Semantic Ambiguity and Underspecification, pp. 101–124. CSLI Publications, Stanford (1996)Google Scholar
  10. 10.
    Buvač, S., Buvač, V., Mason, I.A.: The semantics of propositional contexts. In: Raś, Z.W., Zemankova, M. (eds.) ISMIS 1994. LNCS, vol. 869, pp. 468–477. Springer, Heidelberg (1994). doi: 10.1007/3-540-58495-1_47 CrossRefGoogle Scholar
  11. 11.
    Buvač, S., Buvač, V., Mason, I.A.: Metamathematics of contexts. Fundam. Informaticae 23, 263–301 (1995)MathSciNetzbMATHGoogle Scholar
  12. 12.
    DeRose, K.: Solving the skeptical problem. Philos. Rev. 104, 1–52 (1995)CrossRefGoogle Scholar
  13. 13.
    Dretske, F.I.: Epistemic operators. J. Philos. 67, 1007–1023 (1970)CrossRefGoogle Scholar
  14. 14.
    Gabbay, D.M.: Labelled Deductive Systems, vol. 1. Clarendon Press, Oxford (1996)zbMATHGoogle Scholar
  15. 15.
    Ghidini, C., Giunchiglia, F.: Local models semantics, or contextual reasoning=locality+compatibility. Artif. Intell. 127, 221–259 (2001)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Ghidini, C., Serafini, L.: A context-based logic for distributed knowledge representation and reasoning. In: Bouquet, P., Benerecetti, M., Serafini, L., Brézillon, P., Castellani, F. (eds.) CONTEXT 1999. LNCS (LNAI), vol. 1688, pp. 159–172. Springer, Heidelberg (1999). doi: 10.1007/3-540-48315-2_13 CrossRefGoogle Scholar
  17. 17.
    Ghidini, C., Serafini, L.: Distributed first order logic. Computing Research Repository (CoRR) [cs.LO], pp. 1–89 (2015). arXiv:1507.07755
  18. 18.
    Giunchiglia, F.: Contextual reasoning. Epistemologia 16, 341–364 (1993)Google Scholar
  19. 19.
    Giunchiglia, F., Serafini, L.: Multilanguage hierarchical logics, or: how we can do without modal logics. Artif. Intell. 65, 29–70 (1994)MathSciNetCrossRefzbMATHGoogle Scholar
  20. 20.
    Guha, R., McCarthy, J.: Varieties of contexts. In: Blackburn, P., Ghidini, C., Turner, R.M., Giunchiglia, F. (eds.) CONTEXT 2003. LNCS (LNAI), vol. 2680, pp. 164–177. Springer, Heidelberg (2003). doi: 10.1007/3-540-44958-2_14 CrossRefGoogle Scholar
  21. 21.
    McCarthy, J.: Notes on formalizing context. In: Bajcsy, R. (ed.) Proceedings of the 13th International Joint Conference on Artificial Intelligence (IJCAI), pp. 555–560. Morgan Kaufmann, Chambéry (1993)Google Scholar
  22. 22.
    McCarthy, J., Buvač, S.: Formalizing context (expanded notes). In: Aliseda, A., van Glabbeek, R., Westerståhl, D. (eds.) Computing Natural Language, pp. 13–50. CSLI Publications, Stanford (1997)Google Scholar
  23. 23.
    Serafini, L., Bouquet, P.: Comparing formal theories of context in AI. Artif. Intell. 155, 41–67 (2004)MathSciNetCrossRefzbMATHGoogle Scholar
  24. 24.
    Sowa, J.F.: Knowledge Representation. Logical, Philosophical, and Computational Foundations. Brooks/Cole, Pacific Grove (2000)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Université de SherbrookeSherbrookeCanada

Personalised recommendations