  We address the problem of building a decision model for a specific bidding
situation in the game of Bridge. We propose the following multi-step
methodology i) Build a set of examples for the decision problem and use
simulations to associate a decision to each example ii) Use supervised
relational learning to build an accurate and readable model iii) Perform a
joint analysis between domain experts and data scientists to improve the
learning language, including the production by experts of a handmade model iv)
Build a better, more readable and accurate model.
