Abstract
In order to effectively solve the problem of acquiring knowledge from tactical wargaming data, an overall analysis framework is designed based on the standard process of data mining. The data is analyzed from four aspects: time, space, maneuver path and multi-operator behavior correlation. The behavioral characteristics of single operators at different stages and the spatial distribution of key points such as shooting points, hit points and hidden points, and the association rules of movement, shooting, and occupation between multiple operators are obtained. This will provide commanders with experience and knowledge, help them to quickly accumulate combat experience, and provide behavior rules and action modes for the development of wargaming AI, effectively improving its intelligent level.
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