Fig. 1

System architecture. Figure 1 shows the system architecture. The student and the wizard communicate through Skype to allow the wizard to see the product the student is asking about. In order to provide the wizard with the optimal dialogue strategy, an agent is trained based on a reinforcement learning algorithm, and passes to the wizard the optimal strategy to take at each step. The wizard reports first their state of knowledge to the agent through a web interface (e.g., I do not have any information about the student’s country yet). Once the agent receives the current state of knowledge of the system, it provides the wizard with the appropriate action to take (e.g., ask for the student’s country). If the agent suggests the querying of the associated concept, the wizard retrieves the CSA from a provided database. The database contains food items as well as their related country of origin, the region of origin, the related ingredients, and their usage. The dialogue, directed by the agent and executed by the wizard, is carried out until the CSA is provided to the student and understood by them