基于Agent状态转换的用户内部状态转换在prva中建立信任

T. Matsui, S. Yamada
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引用次数: 6

摘要

在本研究中,我们旨在提出一种设计可信赖的PRVAs(产品推荐虚拟代理)的方法。我们将智能体的可信度定义为受用户情感和人类感知的知识驱动。此外,我们还提出了一个用户内部状态转换模型来增加信任。为了增加信任,我们的目标是通过情绪传染使用户情绪向积极的转变,并通过增加代理的知识使用户感知到的知识变得更高。我们进行了两次实验来检验这个模型。在实验1中,prva推荐旅行团,并且在10个推荐的后半部分变得非常了解。在实验2中,被试者推荐了相同的旅行团,并在后半部分表达了积极的情绪。结果表明,参与者的内心状态发生了预期的转变,证明了该模型对PRVA推荐具有一定的价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Building Trust in PRVAs by User Inner State Transition through Agent State Transition
In this research, we aim to suggest a method for designing trustworthy PRVAs (product recommendation virtual agents). We define an agent's trustworthiness as being operated by user emotion and knowledgeableness perceived by humans. Also, we suggest a user inner state transition model for increasing trust. To increase trust, we aim to cause user emotion to transition to positive by using emotional contagion and to cause user knowledgeableness perceived to become higher by increasing an agent's knowledge. We carried out two experiments to inspect this model. In experiment 1, the PRVAs recommended package tours and became highly knowledgeable in the latter half of ten recommendations. In experiment 2, the PRVAs recommended the same package tours and expressed a positive emotion in the latter half. As a result, participants' inner states transitioned as we expected, and it was proved that this model was valuable for PRVA recommendation.
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