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

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AI*IA 2018 – Advances in Artificial Intelligence (AI*IA 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11298))

Abstract

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 \(\mathcal {ALC}\).

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Notes

  1. 1.

    Here, we focus on the proposal of the formalism itself, therefore the machinery for obtaining probabilities from an application domain will not be discussed.

  2. 2.

    Here we assume that some methods for the automatic assignment of the HEAD/MODIFER pairs are/may be available and focus on the discussion of the reasoning part.

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Acknowledgements

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.

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Authors and Affiliations

  1. Dipartimento di Informatica, Università di Torino, and ICAR-CNR Palermo, Turin, Palermo, Italy

    Antonio Lieto

  2. Dipartimento di Informatica, Università di Torino, Turin, Italy

    Gian Luca Pozzato

Authors
  1. Antonio Lieto
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  2. Gian Luca Pozzato
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Correspondence to Gian Luca Pozzato .

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Editors and Affiliations

  1. Fondazione Bruno Kessler, Povo (TN), Italy

    Chiara Ghidini

  2. Fondazione Bruno Kessler, Povo (TN), Italy

    Bernardo Magnini

  3. University of Trento, Povo (TN), Italy

    Andrea Passerini

  4. Fondazione Bruno Kessler, Povo (TN), Italy

    Paolo Traverso

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Lieto, A., Pozzato, G.L. (2018). Creative Concept Generation by Combining Description Logic of Typicality, Probabilities and Cognitive Heuristics. In: Ghidini, C., Magnini, B., Passerini, A., Traverso, P. (eds) AI*IA 2018 – Advances in Artificial Intelligence. AI*IA 2018. Lecture Notes in Computer Science(), vol 11298. Springer, Cham. https://doi.org/10.1007/978-3-030-03840-3_14

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  • DOI: https://doi.org/10.1007/978-3-030-03840-3_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03839-7

  • Online ISBN: 978-3-030-03840-3

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