Recent technological advancements have increased the likelihood that smart home technologies will become part of our everyday environments. However, many of these technologies are brittle and do not adapt to the user’s wishes or changes in residents’ habits and lifestyle. Here we introduce CASAS, an adaptive smart home that utilizes machine learning techniques to discover patterns in user behavior and to automatically mimic these patterns. Our goal is to keep the resident in control of the automation. Users can provide feedback on proposed automation activities, modify the automation policies, and introduce new requests. In addition, CASAS can discover changes in resident’s behavior patterns automatically. In this paper we describe the CASAS technologies and evaluate its ability to adapt to the resident’s activities and requests.