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Double Dummy Bridge Problem in Contract Bridge:An Overview


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1 Department of Computer Science, Bharathiar University Arts and Science College, Modakkurichi, Erode-638109, Tamil Nadu, India
     

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The bridge game is one of the most commonly known card games comprising many mesmerizing aspects, such as bidding, playing and winning the trick including estimation of human hand strength. The harmonizing input data based on the human knowledge of the game to improvement the quality of results. The game classified under a game of imperfect information is to be equally well-defined, since the decision made on any stage of the game is simply based on the assessment that was made on the immediate preceding stage. The intelligent game of bridge incompleteness of information, the real spirit of the card game in proceeding further deals of the game are taking into many forms especially during the distribution of cards for the next deal. The cascade correlation neural network architecture with supervised learning implemented in resilient back-propagation algorithm to train data and therefore to test it is joined along with the Bamberger point count method and work point count methods. The experimental results reveal that cascade-correlation neural network model with resilient back-propagation algorithm yields better results than back-propagation algorithm.

Keywords

Cascade-Correlation Neural Network, Resilient Back-Propagation Algorithm, Bridge Game, Double Dummy Bridge Problem, Bamberger Point Count Method, Work Point Count Method.
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  • Double Dummy Bridge Problem in Contract Bridge:An Overview

Abstract Views: 339  |  PDF Views: 7

Authors

Dharmalingam Muthusamy
Department of Computer Science, Bharathiar University Arts and Science College, Modakkurichi, Erode-638109, Tamil Nadu, India

Abstract


The bridge game is one of the most commonly known card games comprising many mesmerizing aspects, such as bidding, playing and winning the trick including estimation of human hand strength. The harmonizing input data based on the human knowledge of the game to improvement the quality of results. The game classified under a game of imperfect information is to be equally well-defined, since the decision made on any stage of the game is simply based on the assessment that was made on the immediate preceding stage. The intelligent game of bridge incompleteness of information, the real spirit of the card game in proceeding further deals of the game are taking into many forms especially during the distribution of cards for the next deal. The cascade correlation neural network architecture with supervised learning implemented in resilient back-propagation algorithm to train data and therefore to test it is joined along with the Bamberger point count method and work point count methods. The experimental results reveal that cascade-correlation neural network model with resilient back-propagation algorithm yields better results than back-propagation algorithm.

Keywords


Cascade-Correlation Neural Network, Resilient Back-Propagation Algorithm, Bridge Game, Double Dummy Bridge Problem, Bamberger Point Count Method, Work Point Count Method.

References