I've written my own Reversi player, based on the MiniMax algorithm, with Alpha-Beta pruning, but in the first 10 moves my evaluation function is too slow. I need a good early-game evaluation function.
I'm trying to do it with this matrix (corresponding to the board) which determines how favourable that square is to have:
{ 30, -25, 10, 5, 5, 10, -25, 30,},
{-25, -25, 1, 1, 1, 1, -25, -25,},
{ 10, 1, 5, 2, 2, 5, 1, 10,},
{ 5, 1, 2, 1, 1, 2, 1, 5,},
{ 5, 1, 2, 1, 1, 2, 1, 5,},
{ 10, 1, 5, 2, 2, 5, 1, 10,},
{-25, -25, 1, 1, 1, 1, -25, -25,},
{ 30, -25, 10, 5, 5, 10, -25, 30,},};
But it doesn't work well.
Have you even written an early-game evaluation function for Reversi?