Topic management for an engaging conversational agent

We present an engagement-driven Topic Manager that enables a conversational agent to personalise the topics of interaction in human-agent information-giving chat. The Topic Selection component of this computational model decides what the agent should talk about and when. For this it takes into account the agent's dynamically updated perception of the user's engagement as well as the agent's own mental state. The Topic Transition component of the Topic Manager computes how the agent should introduce the topics in the ongoing interaction without loosing the coherence of the interaction. We have implemented the Topic Manager in a virtual agent, endowing it with the ability to adapt the topics of the interaction on the fly to promote the user's engagement. By means of an evaluation study we have found that third party observers perceive the actions of the Topic Manager in the agent's behaviour.