Example-based Estimation of Hand´s Strength in the Game of Bridge with or without Using Explicit Human Knowledge

The paper presents results of experiments of estimating the number of tricks to be taken by one pair of bridge players in so-called Double Dummy Bridge Problem, using artificial neural networks. In addition to deals presented to neural network´s inputs, also some human methods of estimating strength of a hand were applied. Influence of human knowledge on neural network´s results depends on the way of coding a deal. One of deal representations tested in the paper definitely outperformed all the other choices even when the remaining representations were additionally supported by human knowledge implemented by several estimators frequently used in professional play. This superior representation output a perfect answer in 53.11% of test deals and only in 3.52% of them was mistaken by more than one trick