A "Never-Loose" Strategy to Play the Game of Tic-Tac-Toe
Amarjeet Singh, Kusum Deep, Atulya K. Nagar · 2014
In much of the literature available to solve the tic-tac-toe board game, the common approaches, such as, co evolution, neural networks, evolutionary programming and genetic algorithm are used. In the present work we present a deterministic approach for playing tic-tac-toe game, in which 9 objective functions are defined to decide player's best move. For choosing the best from the solutions generated, by combination of mutating zero as 1, certain axioms are defined. The beauty of this method lies in the fact that if the player decides a move with this method, he never loses the match whenever the player begins the game. We suspect that functions can be defined on the similar grounds for other existing board games and some of this work is in progress and will be reported elsewhere. Some implications on these lines have been made as recommendations in this paper.