Research on static evaluation method for computer game of NoGo

The game of NoGo needs to be optimized its theoretical system and evaluation methods since it is been proposed in recent years. At present, most of the programs of NoGo are based on Monte-Carlo Tree Search (MCTS), but its programs are rarely based on static evaluation algorithm. In this paper, according to the rules and characteristics of NoGo, a static evaluation method has been put forward. In the method, the points on the chessboard of NoGo are classified by the summarized information of the points around them firstly and then the empty points are estimated. The valuation of an empty point is according to its type and the types of the points around it. The sum of the valuations of all empty points on the chessboard is the total evaluation of the chessboard. The experimental results show that the static evaluation method can accurately estimate the value of each state in NoGo.