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Artificial Neural Network Based Adaptive Chess Playing Machine

Author(s): Diwas Sharma | Udit Kr. Chakraborty

Journal: International Journal of Advanced Research in Computer Science
ISSN 0976-5697

Volume: 04;
Issue: 04;
Start page: 87;
Date: 2013;
Original page

Keywords: Artificial | Neural | Network | Championship | game | En | passant | legal | move | Octavius

Various research projects have attempted to build a program that learns to play chess game, given little or no prior knowledge beyond the rule of the game. A typical chess playing engine exhaustively explores the moving possibilities from a chessboard configuration to choose what the next best move to play is. The brute- force method used by the Deep Blue chess machine has made huge impact in the field of artificial intelligence, but is immensely resource hungry. This paper presents a very simple and efficient approach to develop an intelligent chess engine which will hint at the best possible move using the evolutionary and adaptive computing technique on learning from the human grandmasters.
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