author = {Riguzzi, Fabrizio and Bellodi, Elena and Zese, Riccardo and Alberti, Marco and Lamma, Evelina},
  title = {Probabilistic inductive constraint logic},
  journal = {Machine Learning},
  year = {2021},
  volume = {110},
  issue = {4},
  pages = {723-754},
  doi = {10.1007/s10994-020-05911-6},
  pdf = {},
  publisher = {Springer},
  issn = {08856125}
  author = {Marco Alberti and
               Marco Gavanelli and
               Evelina Lamma and
               Fabrizio Riguzzi and
               Ken Satoh and
               Riccardo Zese},
  title = {Dischargeable Obligations in the {SCIFF} Framework},
  journal = {Fundamenta Informaticae},
  volume = {176},
  number = {3-4},
  pages = {321--348},
  year = {2020},
  doi = {10.3233/FI-2020-1976},
  publisher = {IOS Press}
  title = {Improving the Efficiency of Euclidean {TSP} Solving in {Constraint Programming} by Predicting Effective Nocrossing Constraints},
  booktitle = {IPS-RCRA 2020, Italian Workshop on Planning and Scheduling and International Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion},
  year = 2020,
  author = {Elena Bellodi and Alessandro Bertagnon and Marco Gavanelli and Riccardo Zese},
  editor = {Riccardo De Benedictis and Marco Maratea and Andrea Micheli and Enrico Scala and Ivan Serina and Alessandro Umbrico and Mauro Vallati},
  volume = {2745},
  series = {CEUR Workshop Proceedings},
  publisher = {Sun {SITE} Central Europe},
  address = {Aachen, Germany},
  issn = {1613-0073},
  venue = {Online Event},
  eventdate = {November 25-27, 2020},
  copyright = {by the authors},
  url = {},
  pages = {1-15}
  title = {A Framework for Reasoning on Probabilistic Description Logics},
  author = {Cota, Giuseppe and Zese, Riccardo and Bellodi, Elena and Lamma, Evelina and Riguzzi, Fabrizio},
  booktitle = {Applications and Practices in Ontology Design, Extraction, and Reasoning},
  series = {Studies on the Semantic Web},
  volume = {49},
  editor = {Cota, Giuseppe and Daquino, Marilena and Pozzato, Gian Luca},
  isbn = {978-1-64368-142-9},
  doi = {10.3233/SSW200040},
  language = {English},
  pages = {127-144},
  year = {2020},
  publisher = {{IOS} Press},
  abstract = {While there exist several reasoners for Description Logics, very few of them can cope with uncertainty. BUNDLE is an inference framework that can exploit several OWL (non-probabilistic) reasoners to perform inference over Probabilistic Description Logics.
	In this chapter, we report the latest advances implemented in BUNDLE. In particular, BUNDLE can now interface with the reasoners of the TRILL system, thus providing a uniform method to execute probabilistic queries using different settings. BUNDLE can be easily extended and can be used either as a standalone desktop application or as a library in OWL API-based applications that need to reason over Probabilistic Description Logics.
	The reasoning performance heavily depends on the reasoner and method used to compute the probability. We provide a comparison of the different reasoning settings on several datasets.
  copyright = {Akademische Verlagsgesellschaft AKA GmbH, Berlin}
  author = {Elena Bellodi and Marco Alberti and Fabrizio Riguzzi and Riccardo Zese},
  title = {{MAP} Inference for Probabilistic Logic Programming},
  journal = {Theory and Practice of Logic Programming},
  publisher = {Cambridge University Press},
  copyright = {Cambridge University Press},
  year = {2020},
  url = {},
  volume = {20},
  doi = {10.1017/S1471068420000174},
  pdf = {},
  number = {5},
  pages = {641–655}

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