An Improved Chess Machine based on Artificial Neural Networks
Diwas Sharma and Udit Kr. Chakraborty. Article: An Improved Chess Machine based on Artificial Neural Networks. IJCA Proceedings on National Conference cum Workshop on Bioinformatics and Computational Biology NCWBCB(3):8-12, May 2014. Full text available. BibTeX
@article{key:article,
author = {Diwas Sharma and Udit Kr. Chakraborty},
title = {Article: An Improved Chess Machine based on Artificial Neural Networks},
journal = {IJCA Proceedings on National Conference cum Workshop on Bioinformatics and Computational Biology},
year = {2014},
volume = {NCWBCB},
number = {3},
pages = {8-12},
month = {May},
note = {Full text available}
}
Abstract
Numerous published studies revealed that various researchers have attempted to build a program that learns to play cognitive games, given little or no earlier knowledge about the rule of the game. A usual chess playing machine thoroughly explores the moving possibilities from a chessboard configuration to choose what the next best move to make. The brute- force searching technique used by the Deep Blue chess engine has made vast impact in the ground of artificial intelligence, but still found to be resource hungry. This paper, with the concept of Artificial Neural Networks presents a very simple and efficient approach to develop an intelligent chess engine which can assist and hint the possible move within the game using the evolutionary and a adaptive computing technique on learning from the human grandmasters.
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