Construction and Elicitation of a Black Box Model in the Game of Bridge
This work addresses a domain-specific problem in Bridge bidding, presenting an incremental improvement through a hybrid approach.
The paper tackled the problem of building a decision model for a specific bidding situation in Bridge by proposing a multi-step methodology involving simulations, supervised relational learning, and expert collaboration, resulting in a more readable and accurate model.
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.