A Spontaneous Topic Change of Dialogue for Conversational Agent Based on Human Cognition and Memory

Mixed-initiative interaction (MII) plays an important role for the flexible dialogues in conversational agent. Since conventional research on MII process dialogues based on the predefined methodologies, they only provide simple and static dialogues rather than complicated and dynamic dialogues through context-aware themselves. In this paper, we proposed a spontaneous conversational agent that provides MII and can change topics of dialogue dynamically based on human cognitive architecture and memory structure. Based on the global workspace theory, one of the simple cognitive architecture models, the proposed agent is aware of the context of dialogue in conscious level and chooses the topic in unconscious level which is the most relevant to the current context as the next topic of dialogues. We represent the unconscious part of memory using semantic network which is a popular representation for storing knowledge in the field of cognitive science, and retrieve the semantic network according to the spreading activation theory which is proven to be efficient for inferring in semantic networks. It is verified that the proposed method spontaneously changes the topics of dialogues through some dialogue examples on the domain of schedule management.