Strangers and Friends - Adapting the Conversational Style of an Artificial Agent

We demonstrate how an artificial agent’s conversational style can be adapted to different interlocutors by using a model of Person Memory. While other approaches so far rely on adapting an agent’s behavior according to one particular factor like personality or relationship, we show how to enable an agent to take diverse factors into account at once by exploiting social categories. This way, our agent is able to adapt its conversational style individually to reflect interpersonal relationships during conversation.