Abstract
Game strategy planning is a difficult task in Real Time Strategy (RTS) game AI development. Tree searching technique has been one of the common approaches. However, the increasing use of complicated game rules leads to tree models that are huge and complex, and sometimes even unmanageable. Traversing and modification of the tree structure becomes a time consuming and inflexible task. Our research tries to avoid this top-down strategy planning method and propose a bottom-up approach by apply Fuzzy Integral in extracting useful game strategies from data. We also developed a new fuzzy integral for game decision-making. Compared with the traditional Choquet Integral, we achieved a better result using real Warcraft III battle data and the detail is reported in this paper.
