Creative Concept Generation by Combining Description Logic of Typicality, Probabilities and Cognitive Heuristics

  • Antonio Lieto
  • Gian Luca PozzatoEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11298)


We propose a nonmonotonic Description Logic of typicality as a tool for the generation and the exploration of novel creative concepts, that could be useful in many applicative scenarios, ranging from video games to the creation of new movie characters. In particular, our logic is able to deal with the phenomenon of prototypical concept combination, which has been shown to be problematic to model for other formalisms like fuzzy logic. The proposed logic relies on the logic of typicality \(\mathcal {ALC} + \mathbf{T}_\mathbf{R}\), whose semantics is based on a notion of rational closure, as well as on the distributed semantics of probabilistic Description Logics, and takes into account the insights coming from the heuristics used by humans for concept composition. Besides providing framework able to account for typicality-based concept combination, we also outline that reasoning in the proposed Description Logic is ExpTime-complete as for the underlying \(\mathcal {ALC}\).



This work has been partially supported by the project “ExceptionOWL: Nonmonotonic Extensions of Description Logics and OWL for defeasible inheritance with exceptions”, Università di Torino and Compagnia di San Paolo, call 2014 “Excellent (young) PI”. Gian Luca Pozzato has been also partially supported by the project “iNdAM GNCS” - Metodi di prova orientati al ragionamento automatico per logiche non-classiche.


  1. 1.
    Frixione, M., Lieto, A.: Representing concepts in formal ontologies: compositionality vs. typicality effects. Log. Log. Philos. 21(4), 391–414 (2012)Google Scholar
  2. 2.
    Osherson, D.N., Smith, E.E.: On the adequacy of prototype theory as a theory of concepts. Cognition 9(1), 35–58 (1981)CrossRefGoogle Scholar
  3. 3.
    Lieto, A., Pozzato, G.L.: A description logic of typicality for conceptual combination. In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G.A., Raś, Z.W. (eds.) ISMIS 2018. LNCS (LNAI), vol. 11177, pp. 189–199. Springer, Cham (2018). Scholar
  4. 4.
    Giordano, L., Gliozzi, V., Olivetti, N., Pozzato, G.L.: Semantic characterization of rational closure: from propositional logic to description logics. Artif. Intell. 226, 1–33 (2015)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Lehmann, D., Magidor, M.: What does a conditional knowledge base entail? Artif. Intell. 55(1), 1–60 (1992)MathSciNetCrossRefGoogle Scholar
  6. 6.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Reasoning with probabilistic ontologies. In: Yang, Q., Wooldridge, M., (eds.): Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI 2015, Buenos Aires, Argentina, 25–31 July 2015, pp. 4310–4316. AAAI Press (2015)Google Scholar
  7. 7.
    Hampton, J.A.: Inheritance of attributes in natural concept conjunctions. Mem. Cogn. 15(1), 55–71 (1987)CrossRefGoogle Scholar
  8. 8.
    Lieto, A., Minieri, A., Piana, A., Radicioni, D.P.: A knowledge-based system for prototypical reasoning. Connect. Sci. 27, 137–152 (2015)CrossRefGoogle Scholar
  9. 9.
    Hampton, J.A.: Conceptual combinations and fuzzy logic. Concepts Fuzzy Log. 209, 209–232 (2011)Google Scholar
  10. 10.
    Lewis, M., Lawry, J.: Hierarchical conceptual spaces for concept combination. Artif. Intell. 237, 204–227 (2016)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Smith, E.E., Osherson, D.N.: Conceptual combination with prototype concepts. Cogn. Sci. 8(4), 337–361 (1984)CrossRefGoogle Scholar
  12. 12.
    Gärdenfors, P.: The Geometry of Meaning: Semantics Based on Conceptual Spaces. MIT Press, Cambridge (2014)zbMATHGoogle Scholar
  13. 13.
    Nagai, Y., Taura, T.: Formal description of concept-synthesizing process for creative design. In: Gero, J.S. (ed.) Design Computing and Cognition ’06, pp. 443–460. Springer, Dordrecht (2006). Scholar
  14. 14.
    Confalonieri, R., Schorlemmer, M., Kutz, O., Peñaloza, R., Plaza, E., Eppe, M.: Conceptual blending in EL++. In: Lenzerini, M., Peñaloza, R., (eds.): CEUR Workshop Proceedings of the 29th International Workshop on Description Logics, Cape Town, South Africa, 22–25 April 2016, vol. 1577. (2016)Google Scholar
  15. 15.
    Eppe, M., et al.: A computational framework for conceptual blending. Artif. Intell. 256, 105–129 (2018)MathSciNetCrossRefGoogle Scholar
  16. 16.
    Pozzato, G.L.: Reasoning in description logics with typicalities and probabilities of exceptions. In: Antonucci, A., Cholvy, L., Papini, O. (eds.) ECSQARU 2017. LNCS (LNAI), vol. 10369, pp. 409–420. Springer, Cham (2017). Scholar
  17. 17.
    Pozzato, G.L.: Reasoning about plausible scenarios in description logics of typicality. Intell. Artif. 11(1), 25–45 (2017)MathSciNetGoogle Scholar
  18. 18.
    Riguzzi, F., Bellodi, E., Lamma, E., Zese, R.: Probabilistic description logics under the distribution semantics. Semant. Web 6(5), 477–501 (2015)CrossRefGoogle Scholar
  19. 19.
    Giordano, L., Gliozzi, V., Olivetti, N., Pozzato, G.L.: Rational closure in \(\cal{SHIQ}\). In: CEUR Workshop Proceedings DL 2014, 27th International Workshop on Description Logics, vol. 1193, pp. 543–555. (2014)Google Scholar
  20. 20.
    Giordano, L., Gliozzi, V., Pozzato, G.L., Renzulli, R.: An efficient reasoner for description logics of typicality and rational closure. In: Artale, A., Glimm, B., Kontchakov, R., (eds.): CEUR Workshop Proceedings of the 30th International Workshop on Description Logics, Montpellier, France, 18–21 July 2017, vol. 1879. (2017)Google Scholar

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Authors and Affiliations

  1. 1.Dipartimento di InformaticaUniversità di Torino, and ICAR-CNR PalermoTurin, PalermoItaly
  2. 2.Dipartimento di InformaticaUniversità di TorinoTurinItaly

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