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In this work, the benefits of Ambient Intelligence for enhancing user experience with Brain Computer Interfaces are explored. In a smart-home environment, statistics of devices activations are used to learn user habits and to adapt the interface for providing the most usual option to the user, reducing the time spent navigating through hierarchical menus. The activation statistics are learned by discriminative machine learning algorithms able to provide the most suitable options for the user interface. Promising experimental results on simulated scenarios encourage following on this research direction.