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Developers of tomorrow's command and control centers are facing numerous problems related to the vast amount of available information obtained from various sources. On a lower level, huge amounts of uncertain reports from different sensors need to be fused into comprehensible information. On a higher level, representation and management of the aggregated information will be the main task, with prediction of future course of events being the uttermost goal. Unfortunately, traditional agent modeling techniques do not capture situations where commanders make decisions based on other commanders' reasoning about one's own reasoning. To cope with this problem, we propose a decision support tool for command and control situation awareness enhancements based on game theory for inference and coupled with traditional AI methods for uncertainty modeling.