A selective move generator for the game Axis and Allies

We consider the move generation in a modern board game where the set of all the possible moves is too large to be generated. The idea is to provide a set of simple abstract tactics that would generate enough combinations to provide strong opposition. The reduced search space is then traversed using the search. We also propose a technique that allows us to remove the stochasticity from the search space. The model was tested in a game called Axis and Allies: a modern, turn-based, perfect information, non-deterministic, strategy board game. We first show that a tree search technique based on a restrained set of moves can beat the actual scripted AI engine E.Z. FODDER. We can conclude from the experiments that searching deeper generates complex maneuvers which in turn significantly increase the likelihood of victory.