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Augmenting Datalog\(^{\frac{+}{}}\) with Customizable Metalogic Features for Powerful Ontological Reasoning

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AI*IA 2019 – Advances in Artificial Intelligence (AI*IA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11946))

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Abstract

In recent work by Gottlob et al., the usefulness and adequacy of Datalog, and precisely augmented with rules with existential heads to implement ontological reasoning has been shown. Also, it has been shown how to express forms of reasoning that go beyond the expressive capabilities of Description Logics. In our recent work [25] we present a methodology for introducing customizable metalogic features in logic-based knowledge representation and reasoning languages. We made the specific case of Answer Set Programming (ASP), where such features may be part of software engineering toolkits for this programming paradigm. In this paper we show how such metalogic features can further enrich with minor changes to its operational semantics (provided in terms of “chase”) and no additional complexity burden.

Supported by INdAM GNCS-17 and GNCS-19 projects, by project B.I.M.–2018.0419.021, by Univ.of Perugia (projects “ricerca-di-base-2016”, YASMIN, CLTP, and RACRA). Supported by Action COST CA17124 “DigForASP”.

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Notes

  1. 1.

    Recall that, a “fresh” null is a constant that does not occur either in \(\varPi \) or in D.

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Authors and Affiliations

  1. Università di L’Aquila, via Vetoio, 67010, L’Aquila, Italy

    Stefania Costantini

  2. INdAM-GNCS and Università di Perugia, via Vanvitelli 1, 06123, Perugia, Italy

    Andrea Formisano

Authors
  1. Stefania Costantini
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  2. Andrea Formisano
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Correspondence to Andrea Formisano .

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Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Mario Alviano

  2. University of Calabria, Rende, Italy

    Gianluigi Greco

  3. University of Calabria, Rende, Italy

    Francesco Scarcello

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Costantini, S., Formisano, A. (2019). Augmenting Datalog\(^{\frac{+}{}}\) with Customizable Metalogic Features for Powerful Ontological Reasoning. In: Alviano, M., Greco, G., Scarcello, F. (eds) AI*IA 2019 – Advances in Artificial Intelligence. AI*IA 2019. Lecture Notes in Computer Science(), vol 11946. Springer, Cham. https://doi.org/10.1007/978-3-030-35166-3_3

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  • DOI: https://doi.org/10.1007/978-3-030-35166-3_3

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