A Fast Indexing Method for Monte-Carlo Go

3 x 3 patterns are widely used in Monte-Carlo (MC) Go programs to improve the performance. In this paper, we propose a direct indexing approach to build and use a complete 3 x 3 pattern library. The contents of the immediate 8 neighboring positions of a board point are coded into a 16-bit string, called surrounding index. The surrounding indices of all board points can be updated incrementally in an efficient way. We propose an effective method to learn the pattern weights from forty thousand professional games. The method converges faster and performs equally well or better than the method of computing "Elo ratings" [4]. The knowledge contained in the pattern library can be efficiently applied to the MC simulations and to the growth of MC search tree. Testing results showed that our method increased the winning rates of GO INTELLECT against GNU Go on 9 x 9 games by over 7% taking the tax on the program speed into consideration.