Trappy Minimax- using Iterative Deepening to Identify and Set Traps in Two-Player Games

Trappy minimax is a game-independent extension of the minimax adversarial search algorithm that attempts to take advantage of human frailty. Whereas minimax assumes best play by the opponent, trappy minimax tries to predict when an opponent might make a mistake by comparing the various scores returned through iterativedeepening. Sometimes it chooses a slightly inferior move, if there is an indication that the opponent may fall into a trap, and if the potential profit is high. The algorithm was implemented in an Othello program named Desdemona, and tested against both computer and human opponents. Desdemona achieved a higher rating against human opposition on Yahoo! Games when using the trappy algorithm than when it used standard minimax. 1