We describe the Hats Simulator as an information fusion challenge problem. Hats is a virtual world in which many agents engage in individual and collective activities. Most agents are benign, some intend harm. Agent activities are planned by a generative planner. Playing against the simulator, the goal of the analyst is to identify and arrest harmful agents before they carry out their plans. The simulator provides both scalar and categorical information. Information fusion tasks in the Hats domain include assessing information value, choosing information collection strategies, tracking individuals and resources, identifying events, hypothesizing group membership, ascribing suspicion, and identifying plans. After each game, the analyst is assessed a set of scores including the cost of acquiring information, the cost of falsely accusing benign agents, and the cost of failing to detect harmful agents. The simulator is implemented and currently manages hundreds of thousands of agents.