Building a smart home is a multi-disciplinary and challenging problem. Our goal is to build an agent that can propose context aware services to the users. High variability of users' needs and the uniqueness of every home are difficult to handle using "Classical AI". We propose an alternative approach inspired by Developmental Artificial Intelligence and Constructivism Theory. Being constructivist means that the agent builds its knowledge in situ through user's interactions. This continuous interaction process enables the user to customize or bring up the system to meet his personal needs. We have made a first experiment by learning schemas from a simulated two-weeks home scenario. This preliminary experiment gives us indications that Constructivism is a promising approach for ambient intelligence.