The Effects of Depth of Knowledge of a Virtual Agent

Fu-Chia Yang;Kevin Duque;Christos Mousas
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Abstract

We explored the impact of depth of knowledge on conversational agents and human perceptions in a virtual reality (VR) environment. We designed experimental conditions with low, medium, and high depths of knowledge in the domain of game development and tested them among 27 game development students. We aimed to understand how the agent's predefined knowledge levels affected the participants' perceptions of the agent and its knowledge. Our findings showed that participants could distinguish between different knowledge levels of the virtual agent. Moreover, the agent's depth of knowledge significantly impacted participants' perceptions of intelligence, rapport, factuality, the uncanny valley effect, anthropomorphism, and willingness for future interaction. We also found strong correlations between perceived knowledge, perceived intelligence, factuality, and willingness for future interactions. We developed design guidelines for creating conversational agents from our data and observations. This study contributes to the human-agent interaction field in VR settings by providing empirical evidence on the importance of tailoring virtual agents' depth of knowledge to improve user experience, offering insights into designing more engaging and effective conversational agents.
虚拟代理知识深度的影响
我们探索了知识深度对虚拟现实(VR)环境中对话代理和人类感知的影响。我们在游戏开发领域设计了低、中、高知识深度的实验条件,并在 27 名游戏开发专业的学生中进行了测试。我们旨在了解代理的预定知识水平如何影响参与者对代理及其知识的感知。我们的研究结果表明,参与者能够区分虚拟代理的不同知识水平。此外,代理的知识深度极大地影响了参与者对智能、亲和力、事实性、不可思议谷效应、拟人化和未来互动意愿的感知。我们还发现,感知知识、感知智力、事实性和未来互动意愿之间存在很强的相关性。我们根据数据和观察结果制定了创建对话式代理的设计指南。这项研究为虚拟现实环境中的人机交互领域做出了贡献,它提供了实证证据,证明了定制虚拟代理的知识深度对改善用户体验的重要性,为设计更具吸引力和更有效的对话代理提供了启示。
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