Authors : Yaser M. Abid, Alaa Hamza Omaran and Ruqaia Jwad
Abstract: Chess game is considered as the one of the most complex game due to its rules and conditions. It is rather difficult to the beginners to learn all its rules and conditions of movements for each piece in the chess game to be able from playing the game. Today, technologies used to help a human for solving their problems in this study, a smart chessboard designed to guide the players with the next available positions for each piece on the chessboard according to the current position. The proposed smart chessboard trained using neural network with feed forward neural networks algorithms which determine the movements for each piece on the chessboard squares.
Yaser M. Abid, Alaa Hamza Omaran and Ruqaia Jwad, 2018. Supervised Feed Forward Neural Networks for Smart Chessboard Based on FPGA. Journal of Engineering and Applied Sciences, 13: 4093-4098.