在人机交互中的故障情况下形成We意图.
Esteban Guerrero1, Maitreyee Tewari2, Panu Kalmi3
1University of Vaasa, Finland; School of Technology and Innovations, Information Systems Science, Finland.
Computer methods and programs in biomedicine
|October 9, 2023
概括
本研究介绍了一种用于社交机器人和人类形成共享意图 (We-intentions) 和修复故障的计算框架. 该方法旨在通过调整代理目标来改善医疗保健中的人机协作.
科学领域:
- 人与机器人的交互
- 人工智能的人工智能
- 社会机器人社会机器人社会机器人
- 认知科学 认知科学
背景情况:
- 人类和社交机器人之间的联合活动需要共同的群体意图,称为We-intentions.
- 个人和共同意图之间的冲突经常导致崩,特别是在医疗保健机构.
- 解决这些故障对于有效的人机协作至关重要.
研究的目的:
- 在人机交互中引入用于We-intention形成和冲突补偿的计算机制.
- 在医疗保健场景中展示该框架的应用.
- 在共同任务中加强人类和社会机器人之间的意图对齐.
主要方法:
- 使用答案集编程和信念-欲望-意图控制循环开发了一个正式的计算框架.
- 该框架通过涉及人机对话场景的基于理论的用户研究以示例.
- 通过对20名参与者进行半结构面试,收集了定性数据,并以主题分析.
主要成果:
- 证明了四个理论命题,证明了理性社会机器人的理想特征.
- 参与者主要将崩归因于人类的行为.
- 很大一部分年轻的参与者在社交机器人中发现了回避行为.
结论:
- 拟议的框架为代理对齐提供了We-intention理论的新形式化.
- 计算机制确保一致的计划生成,并处理不完整或不一致的意图.
- 定性发现表明,从以人为中心的角度来看,这种方法可以实现可接受的意图协议和赔偿.
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