Ontology-Based Inference for Causal Explanation

  • Ph. Besnard
  • M. -O. Cordier
  • Y. Moinard
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4798)


We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of formal inference patterns from causal statements to explanation statements. These patterns exhibit ontological premises that are argued to be essential in deducing explanation statements. We provide an inference system that captures the patterns discussed.


Inference System Causal Explanation Causal Statement Unary Predicate Sentential Atom 
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.


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  1. 1.
    Baral, C.: Knowledge representation, reasoning and declarative problem solving. Cambridge University Press, Cambridge (2003)zbMATHGoogle Scholar
  2. 2.
    Besnard, Ph., Cordier, M.-O.: Inferring Causal Explanations. In: Hunter, A., Parsons, S. (eds.) ECSQARU 1999. LNCS (LNAI), vol. 1638, pp. 55–67. Springer, Heidelberg (1999)CrossRefGoogle Scholar
  3. 3.
    Bell, J.: Causation as Production. In: Brewka, G., Coradeschi, S., Perini, A., Traverso, P. (eds.) ECAI 2006, pp. 327–331. IOS Press, Riva del Garda, Italy (2006)Google Scholar
  4. 4.
    Bochman, A.: A Logic for Causal Reasoning. In: Gottlob, G., Walsh, T. (eds.) IJCAI 2003, pp. 141–146. Morgan Kaufmann, Acapulco, Mexico (2003)Google Scholar
  5. 5.
    Giunchiglia, E., Lee, J., Lifschitz, V., McCain, N., Turner, H.: Nonmonotonic Causal Theories. Artificial Intelligence 153(1-2), 49–104 (2004)zbMATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Halpern, J., Pearl, J.: Causes and Explanations: A Structural-Model Approach. Part I: Causes. In: Breese, J.S., Koller, D. (eds.) UAI 2001, pp. 194–202. Morgan Kaufmann, Seattle, Wa. (2001)Google Scholar
  7. 7.
    Halpern, J., Pearl, J.: Causes and Explanations: A Structural-Model Approach - Part II: Explanations. In: Nebel, B. (ed.) IJCAI 2001, pp. 27–34. Morgan Kaufmann, Seattle, Wa. (2001)Google Scholar
  8. 8.
    Leone, N., Pfeifer, G., Faber, W., Eiter, T., Gottlob, G., Perri, S., Scarcello, F.: The DLV System for Knowledge Representation and Reasoning. ACM Trans. on Computational Logic (TOCL) 7(3), 499–562 (2006)CrossRefMathSciNetGoogle Scholar
  9. 9.
    Mellor, D.H.: The Facts of Causation. Routledge, London (1995)Google Scholar
  10. 10.
    Shafer, G.: Causal Logic. In: Prade, H. (ed.) ECAI 1998, pp. 711–720. Wiley, Brighton, UK (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Ph. Besnard
    • 1
  • M. -O. Cordier
    • 2
  • Y. Moinard
    • 2
  1. 1.IRIT, CNRS, Université Paul Sabatier, 118 route de Narbonne, 31062 Toulouse cedexFrance
  2. 2.IRISA, INRIA, Université Rennes I, Campus de Beaulieu, 35042 Rennes cedexFrance

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