Abstract:Humans make extensive use of specialized representations to remember people they interacted with. While current research on embodied conversational agents focuses on the relationship between agent and interlocutor, the representation of the latter is mostly neglected. But information about others are inevitable for an agent to adapt to its interlocutors and to establish long-term relationships with them. In this work, we present a model of Person Memory for virtual agents. We discuss what kinds of information have to be stored about people. Furthermore, we stress the importance of social categories. In our scenario, we focus on first encounters between our agent and people. We show how the agent is able to exploit his Person Memory to acquire information about others during Small Talk and guide the conversation.
MOTIVATIONWhen two people meet for the first time they often would like to know from each other: Who are you? How do humans acquire information of others they encounter for the first time? How and what information do they remember from each other? Research on human-like memory for virtual agents has gained a lot of attention recently. Agents equipped with autobiographical memory, e.g. (Kasap et al., 2009), or episodic memory, cf. (Brom et al., 2007, are enabled to remember their own experiences. Companion agents greatly benefit from these memories, in that information from previous interactions can be accessed and used by the agent. However, in the above approaches the memories are centered on the agent's experiences, yet people the agent interacted with play a minor role.In this work we present a model of Person Memory for an embodied conversational agent that focuses on the representation of people. Our agent MAX has a cognitive architecture based on BDI. The agent resides on the hallway of the AI group of Bielefeld University. A broad range of Small Talk knowledge allows for short enjoyable interactions with him. But over the long run, conversations with our agent are more or less the same. So it is not easy to build up some kind of relationship over time, since people may get annoyed by repetitive interactions. To enable our agent to build up longer lasting relationships, he should be put in the position to adapt to his interlocutors. In that, he must be able to distinguish between different kinds of people, in order to know what to talk about. To remember past interactions would allow him to avoid repetition of things already said, and to pick up interesting topics of previous conversations.Small Talk is considered important to increase trust and familiarity (Bickmore and Cassell, 2001) between virtual agents and their interaction partners. Yet, most of the systems equipped with small-talk abilities are restricted to common topics, like the current weather. Small Talk about topics of interest to certain individuals has been mostly neglected. In this paper, we show how information of social categories can be exploited in order to acquire information about, and guide a conversation with, a n...