Learning without human expertise: a case study of the double dummy bridge problem
IEEE Transactions on Neural Networks
A real world application of secure multi-party computations duplicate bridge for cheapskates
Security'08 Proceedings of the 16th International conference on Security protocols
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Compared to other games, particularly chess, the research in computer bridge is immature, and the best bridge-playing programs are mediocre. In this paper we address the problem of designing a fast double-dummy bridge game (i.e., a simplified bridge game with perfect information) solver. Although th size of the game tree we generated for searching the best line of play is huge (about on the order of $13! \cdot 2^{39} \approx 10^{21}$, even if we assume the average branching factor for players to follow suit is just 2), we show that, through varieties of searching techniques and some efficient moves ordering and pruning heuristics, most double-dummy bridge hands can be solved within a reasonable amount of time. In this paper we first give a brief introduction to computer bridge and previous work on the card-playing phase of bridge. Next, we describe the top-level architecture of our double-dummy solver (dds), followed by a number of implementation techniques we employed in our dds. Finally we present experimental results, draw our conclusion and describe some future work toward automating card-playing in real bridge.