Games::AlphaBeta provides a generic implementation of the AlphaBeta
game-tree search algorithm (also known as MiniMax search with alpha beta
pruning). This algorithm can be used to find the best move at a particular
position in any two-player, zero-sum game with perfect information.
Examples of such games include Chess, Othello, Connect4, Go, Tic-Tac-Toe
and many, many other boardgames.

Users must pass an object representing the initial state of the game as the
first argument to new(). This object must provide the following methods:
copy(), apply(), endpos(), evaluate() and findmoves(). This is explained
more carefully in Games::AlphaBeta::Position which is a base class you can
use to implement your position object.

WWW: https://metacpan.org/release/Games-AlphaBeta