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Probabilistic Logical Inference on the Web

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AI*IA 2016 Advances in Artificial Intelligence (AI*IA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10037))

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Abstract

cplint on SWISH is a web application for probabilistic logic programming. It allows users to perform inference and learning using just a web browser, with the computation performed on the server. In this paper we report on recent advances in the system, namely the inclusion of algorithms for computing conditional probabilities with exact, rejection sampling and Metropolis-Hasting methods. Moreover, the system now allows hybrid programs, i.e., programs where some of the random variables are continuous. To perform inference on such programs likelihood weighting is used that makes it possible to also have evidence on continuous variables. cplint on SWISH offers also the possibility of sampling arguments of goals, a kind of inference rarely considered but useful especially when the arguments are continuous variables. Finally, cplint on SWISH offers the possibility of graphing the results, for example by drawing the distribution of the sampled continuous arguments of goals.

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Notes

  1. 1.

    https://dtai.cs.kuleuven.be/problog/.

  2. 2.

    http://swish.swi-prolog.org.

  3. 3.

    http://www.robots.ox.ac.uk/~fwood/anglican/examples/viewer/?worksheet=gaussian-posteriors.

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Acknowledgement

This work was supported by the “GNCS-INdAM”.

Author information

Authors and Affiliations

  1. Dipartimento di Matematica e Informatica, University of Ferrara, Via Saragat 1, 44122, Ferrara, Italy

    Marco Alberti & Fabrizio Riguzzi

  2. Dipartimento di Ingegneria, University of Ferrara, Via Saragat 1, 44122, Ferrara, Italy

    Giuseppe Cota & Riccardo Zese

Authors
  1. Marco Alberti
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  2. Giuseppe Cota
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  3. Fabrizio Riguzzi
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  4. Riccardo Zese
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Corresponding author

Correspondence to Riccardo Zese .

Editor information

Editors and Affiliations

  1. University of Genoa , Genova, Italy

    Giovanni Adorni

  2. University of Parma , Parma, Italy

    Stefano Cagnoni

  3. University of Siena , Siena, Italy

    Marco Gori

  4. University of Genova , Genova, Italy

    Marco Maratea

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Alberti, M., Cota, G., Riguzzi, F., Zese, R. (2016). Probabilistic Logical Inference on the Web. In: Adorni, G., Cagnoni, S., Gori, M., Maratea, M. (eds) AI*IA 2016 Advances in Artificial Intelligence. AI*IA 2016. Lecture Notes in Computer Science(), vol 10037. Springer, Cham. https://doi.org/10.1007/978-3-319-49130-1_26

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  • DOI: https://doi.org/10.1007/978-3-319-49130-1_26

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-49129-5

  • Online ISBN: 978-3-319-49130-1

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