Tic-tac-toe and Fanorona games are ones that can be played at an extremely high level by computer engines. Endgame databases are one of the most powerful parts of these engines. These Endgame databases contain precious informations about how to play the game. Unfortunately, it is quite impossible for human players to learn the game strategies from endgame databases, which are only made of raw sequences of bits. The work presented here is the use of genetic algorithms to extract human friendly knowledge from these databases.