Would a robot trust you? Developmental robotics model of trust and theory of mind
Would a robot trust you? Developmental robotics model of trust and theory of mind
复制标题
机器人会信任你吗？
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
A. Cangelosi
中科院分区：
文献类型：
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作者：
Samuele Vinanzi;Massimiliano Patacchiola;A. Chella;A. Cangelosi
信任是人机交互中的一个关键问题：随着机器人系统变得越来越复杂，通过最大限度地提高其可接受性和可靠性来融入我们的社会变得至关重要。各种研究都研究了人们如何将信任归因于机器人，但很少有人研究相反的情况，即机器人是委托人，人类是受托人。智能体评估其信息源可信度的能力在人和机器人必须合作以实现共同目标的联合任务情况下特别有用。我们提出了一个人工认知架构的基础上，发展机器人的范例，可以估计其人类互动者的可信度的决策。这是通过使用心理理论（ToM）来实现的，心理理论是一种将可能与自己不同的信念和意图分配给他人的心理能力。我们的工作集中在一个类人机器人的认知架构，集成了概率的心理理论和信任模型支持的情景记忆系统。我们在一个成熟的发展心理学实验上测试了我们的架构，取得了与儿童相同的结果，从而展示了一种提高人类和机器人协作质量的新方法。这篇文章是“从社会大脑到社会机器人：将神经认知见解应用于人机交互”主题的一部分。
Trust is a critical issue in human–robot interactions: as robotic systems gain complexity, it becomes crucial for them to be able to blend into our society by maximizing their acceptability and reliability. Various studies have examined how trust is attributed by people to robots, but fewer have investigated the opposite scenario, where a robot is the trustor and a human is the trustee. The ability for an agent to evaluate the trustworthiness of its sources of information is particularly useful in joint task situations where people and robots must collaborate to reach shared goals. We propose an artificial cognitive architecture based on the developmental robotics paradigm that can estimate the trustworthiness of its human interactors for the purpose of decision making. This is accomplished using Theory of Mind (ToM), the psychological ability to assign to others beliefs and intentions that can differ from one’s owns. Our work is focused on a humanoid robot cognitive architecture that integrates a probabilistic ToM and trust model supported by an episodic memory system. We tested our architecture on an established developmental psychological experiment, achieving the same results obtained by children, thus demonstrating a new method to enhance the quality of human and robot collaborations. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
影响因子：
4.6
作者：
Vanderbilt KE;Liu D;Heyman GD
通讯作者：
Heyman GD