不对称的沟通:人类对安卓机器人的认知模型
Daisuke Kawakubo1, Masaki Shuzo1, Hiroaki Sugiyama2
1Tokyo Denki University, Tokyo, Japan.
Frontiers in robotics and AI
|January 29, 2024
概括
这项研究介绍了安卓机器人的不对称沟通策略,将其人格适应客户,而不预测偏好. 这种方法增强了人机交互,并在服务环境中带来了积极的用户体验.
科学领域:
- 人与机器人的交互
- 人工智能的人工智能
- 机器人技术 机器人技术 机器人技术
背景情况:
- 在安卓机器人中实现类似人类的沟通是对话系统的关键目标.
- 感知上的差异是因为人类对待机器人可能不同于其他人类,从而造成不对称的沟通.
- 了解用户接受和优化机器人行为对于有效的人机交互至关重要.
研究的目的:
- 在旅游指南场景中,提出和评估安卓机器人的不对称通信策略.
- 通过在没有明确偏好估计的情况下调整机器人的个性来提高用户的接受度和满意度.
- 开发一种用于评估人机对话中不对称的沟通策略的实验方法.
主要方法:
- 开发了一个不对称的沟通策略,涉及人格适应而不是偏好估计.
- 创建了一个模拟对话实验,使用视频剪辑来评估战略.
- 参与者填写了调查问卷,评估他们对模拟销售员的看法和对待.
主要成果:
- 实验方法有效地评估了参与者治疗和策略的有效性.
- 一次演示显示,29名参观者对Android机器人的战略产生了积极的印象和高度满意.
- 不对称的沟通策略被用户积极看待.
结论:
- 非对称的沟通策略,特别是人格适应,可以改善人机交互.
- 拟议的战略提供了一种可行的方法,用于增强服务角色中的安卓机器人用户体验.
- 进一步的研究可以建立在这种方法上,以完善机器人的沟通和接受.
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