DocumentCode :
162609
Title :
Back-Propagation Neural Network Architecture for Solving the Double Dummy Bridge Problem in Contract Bridge
Author :
Dharmalingam, M. ; Amalraj, R.
Author_Institution :
Dept. of Math. & Comput. Sci. Sri Vasavi Coll., Bharathiar Univ. Coimbatore, Erode, India
fYear :
2014
fDate :
6-7 March 2014
Firstpage :
454
Lastpage :
461
Abstract :
Contract Bridge is an intelligent game, which increases the expose with multiple skills and knowledge because no player knows exactly what moves other players are capable of making. The ´Bridge´, being a game of imperfect information, is to be equally well defined, since the outcome at any intermediate stage is purely based on the decision made on the immediate preceding stage. The credits accumulated by one pair of bridge players towards the target in a fixed number of ´tricks´ is called Double Dummy Bridge Problem. The Back-propagation neural network architecture is used to take the best tricks in Double Dummy Bridge Problem. In summary, the study described in this paper provides a detailed comparison between two different activation functions which were used to train and test the data, hence their behavior in different situations.
Keywords :
backpropagation; decision making; game theory; neural net architecture; backpropagation neural network architecture; contract bridge; decision making; double dummy bridge problem; intelligent game; Artificial neural networks; Biological neural networks; Bridges; Contracts; Games; Neurons; Training; ANN; Activation functions; BPN; Bidding; DDBP; Playing; Supervised Learning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computing Applications (ICICA), 2014 International Conference on
Conference_Location :
Coimbatore
Type :
conf
DOI :
10.1109/ICICA.2014.99
Filename :
6965091
Link To Document :
بازگشت