There are a lot of programs that do parameter learning for Bayes nets. I am having a hard time finding libraries or tools that do (or try to do) structure learning. Specifically, one that uses an information theoretic approach, by looking at the information gain from adding an edge, or analyzing the cross entropy across Random Variables to determine if they have any relationships or are independent. This is not the core problem I am trying to work on, but learning structure is an important part of it. So finding an existing tool/library would help immensely.
Try the bnlearn library. It contains structure learning, parameter learning, inference and various well-known example datasets such as Sprinkler, Asia, Alarm.