cplint on SWISH is a web application for trying probabilistic logic programming. It was written by .

Please use this forum for questions or send an email to cplint@googlegroups.com.

The cplint on SWISH source is available from Github. It requires SWI-Prolog 7 installed from the latest GIT. We also provide a Docker image.

The cplint source is available from Github.

The source for using R in cplint was developed by Franco Masotti and is available from source is available from Github.

cplint on SWISH is described in:

PLP book cover

The algorithm for exact probabilistic inference (PITA) is described in:

The algorithm for Monte Carlo inference (MCINTYRE) is described in:

The algorithm for Metropolis/Hastings sampling is described in:

The algorithm for parameter learning (EMBLEM) is described in:

The SLIPCOVER algorithm for structure learning is described in:

The LEMUR algorithm for structure learning is described in:

SWISH was originally written by Torbjörn Lager as a homage to SWI-Prolog. Jan Wielemaker designed and implemented the present version. The current SWISH application targets primarily at collaborative exploration of data. SWISH can be combined with e.g., CQL to explore relational (SQL) databases or sparkle to explore linked data. A ClioPatria plugin adds Prolog based exploration of RDF data to ClioPatria.

SWISH is a great tool for teaching Prolog. We provide a prototype of Learn Prolog Now! where SWISH is embedded to run examples and solve excercises from within your browser. Peter Flach prepared his book Simply Logical for SWISH.

The SWISH source is available from GitHub. It is under heavy development and often requires SWI-Prolog 7 installed from the latest GIT. We also provide a Docker image.

Avatar graphics created by Noble Master Games, designed by Mei-Li Nieuwland.

The SWISH source is available from Github.

SWISH is described in:

The development of SWISH as a DataLab is sponsored by the COMMIT/ consortium and VRE4EIC.