The main points of this tag is the renaming of *Markov network* (`MarkovNet`, `MN`) for the better known *Markov Random Field* (`MarkovRandomField`, `MRF`) and a new reader/writer of XDSL format (Genie/Smile) for Bayesian networks. Other improvements and corrections have naturally also been made. * aGrUM * Renaming `gum::MarkovNet` to `gum::MarkovRandomField`. Renaming `gum::*MN*` to `gum::*MRF*` when necessary. * Fixing glitches and bugs induced or revealed by `gum::MarkovNet`->`gum::MarkovRandomField`. * new `XDSL` Reader/writer for Bayesian network. * Renaming `gum::Learning::BNLearner::learnMixedStructure` to `gum::Learning::BNLearner::learnPDAG` * working on documentation : better rendering for doxygen pages. * Renaming `gum::dSeparation` to `gum::dSeparationAlgorithm`. * pyAgrum * Renaming `pyAgrum.MarkovNet` to `pyAgrum.MarkovRandomField`. Renaming `pyAgrum.*MN*` to `pyAgrum.*MRF*` when necessary. * new `XDSL` Reader/writer for Bayesian network. * Renaming `pyAgrum.BNLearner.learnMixedStructure()` to `pyAgrum.BNLearner.learnPDAG()`. * For figure containing nodes drawn by matplotlib (e.g. inference), use the same font for all nodes (default from matplotlib) (thanks to Jonathon Blackford). * Working on documentation : better rendering for readthedocs pages, improved structuration, new thumbnail image for some notebooks/tutorials. * Significant improvement of the documentation coverage. * Improving `gum.DiscreteVariable.to[typeOfVariable]`, renaming as `gum.DiscreteVariable.as[typeOfVariable]` and adding documentations.