Tinker: a relational agent museum guide

作者:Timothy W. Bickmore, Laura M. Pfeifer Vardoulakis, Daniel Schulman

摘要

A virtual museum guide agent that uses human relationship-building behaviors to engage museum visitors is described. The computer animated agent, named “Tinker”, uses nonverbal conversational behavior, empathy, social dialogue, reciprocal self-disclosure and other relational behavior to establish social bonds with users, and encourage continued interaction and repeated visits. Tinker describes exhibits in the museum, gives directions, and discusses technical aspects of her own implementation. Tinker also recognizes returning visitors through biometric analysis of their hand shapes and dialogue cues. Results from two experiments using Tinker are described. In the first, 29 returning visitors are randomized to interact with the agent with the biometric identification turned on or off. In the second experiment, 1,607 visitors are randomized to interact with versions of Tinker that have relationship-building behavior turned on or off. Results indicate that the use of relational behavior leads to significantly greater engagement by museum visitors, measured by session length, number of sessions, and self-reported attitude, as well as learning gains, as measured by a knowledge test, compared to the same agent that does not use relational behavior. Implications for museum exhibits and intelligent tutoring systems are discussed.

论文关键词:Relational agents, Social interfaces, Interactive installation, Embodied conversational agent, Intelligent virtual agent, Pedagogical agent, Intelligent tutoring system

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论文官网地址:https://doi.org/10.1007/s10458-012-9216-7