Yegnanarayana, B. ; Khemani, Deepak ; Sarkar, Manish (1996) Neural networks for contract bridge bidding Sadhana (Academy Proceedings in Engineering Sciences), 21 (3). pp. 395-413. ISSN 0256-2499
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Official URL: http://www.ias.ac.in/j_archive/sadhana/21/3/395-41...
Related URL: http://dx.doi.org/10.1007/BF02745531
Abstract
The objective of this study is to explore the possibility of capturing the reasoning process used in bidding a hand in a bridge game by an artificial neural network. We show that a multilayer feedforward neural network can be trained to learn to make an opening bid with a new hand. The game of bridge, like many other games used in artificial intelligence, can easily be represented in a machine. But, unlike most games used in artificial intelligence, bridge uses subtle reasoning over and above the agreed conventional system, to make a bid from the pattern of a given hand. Although it is difficult for a player to spell out the precise reasoning process he uses, we find that a neural network can indeed capture it. We demonstrate the results for the case of one-level opening bids, and discuss the need for a hierarchical architecture to deal with bids at all levels.
Item Type: | Article |
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Source: | Copyright of this article belongs to Indian Academy of Sciences. |
Keywords: | Artificial Neural Networks; Backpropagation; Games; Contract Bridge Bidding; Knowledge; Artificial Intelligence |
ID Code: | 57788 |
Deposited On: | 29 Aug 2011 11:51 |
Last Modified: | 18 May 2016 09:04 |
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