The bridge game is one of the most generally 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 tricks. The bridge game classification under a game of imperfect information is to be equally well-defined. 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 data it is together along with the bamberger point count method and work point count methods.

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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