Construction and Elicitation of a Black Box Model in the Game of Bridge
摘要
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 interpretable 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) Use insights from iii) to learn an almost self-explaining and accurate model.