author = {Marco Alberti and Marco Gavanelli and Evelina Lamma and Fabrizio Riguzzi and Sergio Storari},
  title = {Learning specifications of interaction protocols and business processes and proving their properties},
  journal = {Intelligenza artificiale},
  year = 2011,
  volume = 5,
  number = 1,
  pages = {71--75},
  month = feb,
  doi = {10.3233/IA-2011-0006},
  issn = {1724-8035},
  abstract = {In this paper, we overview our recent research
  activity concerning the induction of Logic Programming
  specifications, and the proof of their properties via Abductive
  Logic Programming. Both the inductive and abductive tools here
  briefly described have been applied to respectively learn and verify
  (properties of) interaction protocols in multi-agent systems, Web
  service choreographies, careflows and business processes.},
  pdf = {}
  author = {Marco Alberti and Elena Bellodi and Giuseppe Cota and
  Fabrizio Riguzzi and Riccardo Zese},
  title = {\texttt{cplint} on {SWISH}: Probabilistic Logical Inference with a Web Browser},
  journal = {Intelligenza Artificiale},
  publisher = {IOS Press},
  copyright = {IOS Press},
  year = {2017},
  issn-print = {1724-8035},
  issn-online = {2211-0097},
  url = {},
  abstract = {
\texttt{cplint} on SWISH is a web application that allows users to
perform reasoning tasks on probabilistic logic programs.
Both inference and learning systems can be performed: 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 and particle filtering are used.
\texttt{cplint} on SWISH is also able to sample goals' arguments and
to graph the results. This paper reports on advances and new features
of \texttt{cplint} on SWISH, including the capability of drawing the
binary decision diagrams created during the inference processes.
  keywords = { Logic Programming, Probabilistic Logic Programming,
Distribution Semantics, Logic Programs with Annotated Disjunctions, Web
  volume = {11},
  number = {1},
  doi = {10.3233/IA-170106},
  pages = {47--64},
  wos = {WOS:000399736500004}
  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}
  author = {Riguzzi, Fabrizio and Bellodi, Elena and Zese, Riccardo and Alberti, Marco and Lamma, Evelina},
  title = {Probabilistic inductive constraint logic},
  journal = {Machine Learning},
  year = {2020},
  pages = {1-32},
  doi = {10.1007/s10994-020-05911-6},
  pdf = {},
  publisher = {Springer},
  issn = {08856125}
  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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