Abstract : THE AUTHORS ARE EXTREMELY GRATEFUL TO GRID5000 for helping in designing and experimenting around Monte-Carlo Tree Search. In order to promote computer Go and stimulate further development and research in the field, the event activities, "Computational Intelligence Forum" and "World 99 Computer Go Championship," were held in Taiwan. This study focuses on the invited games played in the tournament, "Taiwanese Go players versus the computer program MoGo," held at National University of Tainan (NUTN). Several Taiwanese Go players, including one 9-Dan professional Go player and eight amateur Go players, were invited by NUTN to play against MoGo from August 26 to October 4, 2008. The MoGo program combines All Moves As First (AMAF)/Rapid Action Value Estimation (RAVE) values, online "UCT-like" values, offline values extracted from databases, and expert rules. Additionally, four properties of MoGo are analyzed including: (1) the weakness in corners, (2) the scaling over time, (3) the behavior in handicap games, and (4) the main strength of MoGo in contact fights. The results reveal that MoGo can reach the level of 3 Dan with, (1) good skills for fights, (2) weaknesses in corners, in particular for "semeai" situations, and (3) weaknesses in favorable situations such as handicap games. It is hoped that the advances in artificial intelligence and computational power will enable considerable progress in the field of computer Go, with the aim of achieving the same levels as computer chess or Chinese chess in the future.