We consider the problem of dialogue adaptation in our Smart Personal Assistant (SPA), which uses a plan-based dialogue model. We present a novel way of integrating learning into a BDI architecture so the agent can learn to select the most suitable plan amongst those applicable, enabling the SPA to tailor its responses according to the conversational context and the user's physical context, device and preferences. Categories and Subject Descriptors I.2.1 [Artificial Intelligence]: Applications and Expert Systems--natural language interfaces; I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence--intelligent agents General Terms Human Factors Keywords BDI agents, dialogue management, adaptive dialogue systems, symbolic machine learning