I read about minimax, then alpha-beta pruning and then about iterative deepening. Iterative deepening coupled with alpha-beta pruning proves to quite efficient as compared alpha-beta alone.
I have implemented a game agent that uses iterative deepening with alpha-beta pruning. Now I want to beat myself. What can I do to go deeper? Like alpha-beta pruning cut the moves, what other small change could be implemented that can beat my older AI?
My aim to go deeper than my current AI. If you want to know about the game, here is a brief summary:
There are two players, four game pieces and a 7-by-7 grid of squares. At the beginning of the game, the first player places both the pieces on any two different squares. From that point on, the players alternate turns moving both the pieces like a Queen in chess (any number of open squares vertically, horizontally, or diagonally). When the piece is moved, the square that was previously occupied is blocked. That square can not be used for the remainder of the game. The piece can not move through blocked squares. The first player who is unable to move any one of the queens loses.
So my aim is to cut the unwanted nodes and search deeper.