The Game Method of Checkers based on Alpha-Beta Search Strategy with Iterative Deepening

With the game of checkers board games, this paper proposes an algorithm based on the alpha-beta search and iterative deepening optimization. Through adjusting the search depth dynamically, we have solved the problems caused by changes in chess. Also, this paper designs a kind of zoning evaluation function considering pawn difference, in which the board is divided into six regions and assessed respectively. To quantify the pawn difference, experiments are conducted to get the reasonable scaling factor of the king and ordinary.