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CON-HUMO focuses on novel concepts for automatic control, based on data-driven human models and machine learning. This enables innovative control applications that are difficult if not impossible to realize using traditional control and identification methods, in particular in the challenging area of smart human-machine interaction. In order to achieve intuitive and efficient goal-oriented interaction, anticipation is a key. For control selection based on prediction, a dynamic model of the human interaction behavior is required, which, however, is difficult to obtain from first principles.