Neural networks compete with expert human players in solving the Double Dummy Bridge Problem

摘要

Artificial neural networks, trained only on sample bridge deals, without presentation of any human knowledge as well as the rules of the game, are applied to solving the Double Dummy Bridge Problem (DDBP). The problem, in its basic form, consist in estimation of the number of tricks to be taken by one pair of bridge players. The efficacy of knowledge-free neural network approach is compared with the case of applying human estimators of bridge hands' strengths (typically used by professional players) as additional input information. Furthermore, a comparison with the results obtained by 24 professional human bridge players - members of The Polish Bridge Union - on sample test sets is presented, leading to interesting observations about suitability of particular types of deals for artificial systems and for human bridge players.