Training child helpline counsellors with a BDI-based conversational agent

Counsellors at the child helpline offer a confidential environment for children to be heard and empowered. However, training counsellors on handling children’s conversations in text-based chat can be costly and time-consuming. This paper introduces Lilobot, a conversational agent designed for training counsellors of child helplines. The agent’s dialogue is built on the Belief-Desire-Intention (BDI) model, which, in this case, simulates a child victim of school bullying in a text based interaction. Trainees engage with Lilobot in a role-play format, taking on the counsellor’s role. This interactive system helps trainees learn the Five Phase Model, a conversation protocol child’s helplines use. The system also has a trainer interface, where a trainer can oversee and control Lilobot’s interactions, and see a suggested optimal conversational path. The system was built with three main components - a natural language processing model (using Rasa) and the BDI reasoning model and optimal path generation (using Java Spring).