Abstract
This paper is focused on a Double Dummy Bridge Problem (DDBP) which consists in answering the question of how many tricks are to be taken by a pair of players assuming perfect play of all four sides with all cards being revealed. Several experiments are also presented in a variant of DDBP in which the information about to whom of the two players in a given pair a particular card belongs to is hidden. In contrast to our previous works, which were devoted to no trump contracts, here we concentrate on suit contracts. Several interesting conclusions are drawn from comparison of weight patterns of networks trained on no trump contracts only vs. those trained exclusively on suit contracts. The ultimate goal of this research is to construct a computer program playing the game of contract bridge using neural networks and other CI techniques with the basic assumption of using zero-human-knowledge approach and to learn purely on examples.
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References
Kohle, M., Schonbauer, F.: Experience gained with a neural network that learns to play bridge. In: 5th Austrian Artificial Intelligence Meeting, pp. 224–229 (1995)
Sarkar, M., Yegnanarayana, B., Khemani, D.: Application of neural network in contract bridge bidding. In: Proc. of National Conf. on Neural Networks and Fuzzy Systems, Anna University, Madras, pp. 144–151 (1995)
Smith, S., Nau, D., Throop, T.: Computer bridge: A big win for AI planning. AI Magazine 19, 93–106 (1998)
Frank, I., Basin, D.A.: Search in games with incomplete information: A case study using bridge card play. Artificial Intelligence 100(1-2), 87–123 (1998)
Ginsberg, M.: Gib: Imperfect information in a computationally challenging game. Journal of Artificial Intelligence Research 14, 303–358 (2001)
Wheen, R.: Brute force programming for solving double dummy bridge problems. In: Levy, D., Beal, D. (eds.) Heuristic Programming in Artificial Intelligence: the first computer olympiad, pp. 88–94, Ellis Horwood, Chichester (1989)
Mossakowski, K., Mańdziuk, J.: Artificial neural networks for solving double dummy bridge problems. In: Rutkowski, L., Siekmann, J.H., Tadeusiewicz, R., Zadeh, L.A. (eds.) ICAISC 2004. LNCS (LNAI), vol. 3070, pp. 915–921. Springer, Heidelberg (2004)
Mańdziuk, J., Mossakowski, K.: Looking inside neural networks trained to solve double-dummy bridge problems. In: 5th Game-On International Conference on Computer Games: Artificial Intelligence, Design and Education (CGAIDE 2004), Reading, UK, pp. 182–186 (2004)
Mossakowski, K., Mańdziuk, J.: Weight patterns in the networks trained to solve double dummy bridge problem. In: Hryniewicz, O., et al. (eds.) Issues in Intelligent Systems. Paradigms, EXIT, pp. 155–165 (2005)
Ginsberg, M.: http://www.cirl.uoregon.edu/ginsberg/gibresearch.html
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Mossakowski, K., Mańdziuk, J. (2006). Neural Networks and the Estimation of Hands’ Strength in Contract Bridge. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_124
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DOI: https://doi.org/10.1007/11785231_124
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35748-3
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