  We present a general algorithm to order moves so as to speedup exact game
solvers. It uses online learning of playout policies and Monte Carlo Tree
Search. The learned policy and the information in the Monte Carlo tree are used
to order moves in game solvers. They improve greatly the solving time for
multiple games.
