Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer Functions
Sai Ho Ling, Hak Keung Lam
DOI: 10.4236/jilsa.2011.31005   PDF    HTML     8,910 Downloads   18,038 Views   Citations


Computational intelligence is a powerful tool for game development. In this paper, an algorithm of playing the game Tic-Tac-Toe with computational intelligence is developed. This algorithm is learned by a Neural Network with Double Transfer functions (NNDTF), which is trained by genetic algorithm (GA). In the NNDTF, the neuron has two transfer functions and exhibits a node-to-node relationship in the hidden layer that enhances the learning ability of the net-work. A Tic-Tac-Toe game is used to show that the NNDTF provide a better performance than the traditional neural network does.

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S. Ling and H. Lam, "Playing Tic-Tac-Toe Using Genetic Neural Network with Double Transfer Functions," Journal of Intelligent Learning Systems and Applications, Vol. 3 No. 1, 2011, pp. 37-44. doi: 10.4236/jilsa.2011.31005.

Conflicts of Interest

The authors declare no conflicts of interest.


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