Adapting Propositional Cases Based on Tableaux Repairs Using Adaptation Knowledge

  • Gabin Personeni
  • Alice Hermann
  • Jean Lieber
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8765)


Adaptation is a step of case-based reasoning that aims at modifying a source case (representing a problem-solving episode) in order to solve a new problem, called the target case. An approach to adaptation consists in applying a belief revision operator that modifies minimally the source case so that it becomes consistent with the target case. Another approach consists in using domain-dependent adaptation rules. These two approaches can be combined: a revision operator parametrized by the adaptation rules is introduced and the corresponding revision-based adaptation uses the rules to modify the source case. This paper presents an algorithm for revision-based and rule-based adaptation based on tableaux repairs in propositional logic: when the conjunction of source and target cases is inconsistent, the tableaux method leads to a set of branches, each of them ending with clashes, and then, these clashes are repaired (thus modifying the source case), with the help of the adaptation rules. This algorithm has been implemented in the Revisor/PLAK tool and some implementation issues are presented.


Case-based reasoning adaptation tableaux repairs propositional logic belief revision adaptation rules 


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  1. 1.
    Riesbeck, C.K., Schank, R.C.: Inside Case-Based Reasoning. Lawrence Erlbaum Associates, Inc., Hillsdale (1989)Google Scholar
  2. 2.
    Aamodt, A., Plaza, E.: Case-based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications 7(1), 39–59 (1994)Google Scholar
  3. 3.
    Minor, M., Bergmann, R., Görg, S., Walter, K.: Towards Case-Based Adaptation of Workflows. In: Bichindaritz, I., Montani, S. (eds.) ICCBR 2010. LNCS, vol. 6176, pp. 421–435. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  4. 4.
    Manzano, S., Ontañón, S., Plaza, E.: Amalgam-Based Reuse for Multiagent Case-Based Reasoning. In: Ram, A., Wiratunga, N. (eds.) ICCBR 2011. LNCS, vol. 6880, pp. 122–136. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  5. 5.
    Coman, A., Muñoz-Avila, H.: Diverse plan generation by plan adaptation and by first-principles planning: A comparative study. In: Díaz-Agudo, B., Watson, I. (eds.) ICCBR 2012. LNCS, vol. 7466, pp. 32–46. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Rubin, J., Watson, I.: Opponent type adaptation for case-based strategies in adversarial games. In: Díaz-Agudo, B., Watson, I. (eds.) ICCBR 2012. LNCS, vol. 7466, pp. 357–368. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Lieber, J.: Application of the Revision Theory to Adaptation in Case-Based Reasoning: The Conservative Adaptation. In: Weber, R.O., Richter, M.M. (eds.) ICCBR 2007. LNCS (LNAI), vol. 4626, pp. 239–253. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. 8.
    Cojan, J., Lieber, J.: Applying belief revision to case-based reasoning. In: Prade, H., Richard, G. (eds.) Computational Approaches to Analogical Reasoning: Current Trends. SCI, vol. 548, pp. 133–162. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  9. 9.
    Alchourrón, C.E., Gärdenfors, P., Makinson, D.: On the Logic of Theory Change: partial meet functions for contraction and revision. Journal of Symbolic Logic 50, 510–530 (1985)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Cojan, J., Lieber, J.: An Algorithm for Adapting Cases Represented in an Expressive Description Logic. In: Bichindaritz, I., Montani, S. (eds.) ICCBR 2010. LNCS, vol. 6176, pp. 51–65. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  11. 11.
    Schwind, C.: From Inconsistency to Consistency: Knowledge Base Revision by Tableaux Opening. In: Kuri-Morales, A., Simari, G.R. (eds.) IBERAMIA 2010. LNCS, vol. 6433, pp. 120–132. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Melis, E., Lieber, J., Napoli, A.: Reformulation in Case-Based Reasoning. In: Smyth, B., Cunningham, P. (eds.) EWCBR 1998. LNCS (LNAI), vol. 1488, pp. 172–183. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  13. 13.
    Personeni, G., Hermann, A., Lieber, J.: Adapting propositional cases based on tableaux repairs using adaptation knowledge – extended report (2014),
  14. 14.
    Marquis, P., Sadaoui, S.: A new algorithm for computing theory prime implicates compilations. In: AAAI/IAAI, vol. 1, pp. 504–509 (1996)Google Scholar
  15. 15.
    Katsuno, H., Mendelzon, A.: Propositional knowledge base revision and minimal change. Artificial Intelligence 52(3), 263–294 (1991)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Pearl, J.: Heuristics – Intelligent Search Strategies for Computer Problem Solving. Addison-Wesley Publishing Co., Reading (1984)Google Scholar
  17. 17.
    Eiter, T., Gottlob, G.: On the Complexity of Propositional Knowledge Base Revision, Updates, and Counterfactuals. Artificial Intelligence 57, 227–270 (1992)MathSciNetCrossRefzbMATHGoogle Scholar
  18. 18.
    Gent, I., Petrie, K., Puget, J.-F.: Symmetry in constraint programming. In: Rossi, F., van Beek, P., Walsh, T. (eds.) Handbook for Constraint Programming, ch. 10, pp. 329–376. Elsevier (2006)Google Scholar
  19. 19.
    Peppas, P.: Belief Revision. In: van Harmelen, F., Lifschitz, V., Porter, B. (eds.) Handbook of Knowledge Representation, ch. 8, pp. 317–359. Elsevier (2008)Google Scholar
  20. 20.
    Konieczny, S., Pino Pérez, R.: Merging information under constraints: a logical framework. Journal of Logic and Computation 12(5), 773–808 (2002)MathSciNetCrossRefzbMATHGoogle Scholar
  21. 21.
    Cojan, J., Lieber, J.: Belief Merging-Based Case Combination. In: McGinty, L., Wilson, D.C. (eds.) ICCBR 2009. LNCS, vol. 5650, pp. 105–119. Springer, Heidelberg (2009)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Gabin Personeni
    • 1
    • 2
    • 3
  • Alice Hermann
    • 1
    • 2
    • 3
  • Jean Lieber
    • 1
    • 2
    • 3
  1. 1.Université de Lorraine, LORIA, UMR 7503Vandœuvre-lès-NancyFrance
  2. 2.CNRSVandœuvre-lès-NancyFrance
  3. 3.InriaVillers-lès-NancyFrance

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