We propose a method to integrate face-work, a common social ritual related to trust, into a decision-making agent that works collaboratively with a human. Face-work is a set of trust-building behaviors designed to "save face" or prevent others from "losing face." This paper describes the design of a decision-making process that explicitly considers face-work as part of its action selection. We also present a simulated robot arm deployed in an online environment that can be used to evaluate the proposed method.
@article{arxiv.2011.01969,
title = {Face-work for Human-Agent Joint Decision-Making},
author = {JiHyun Jeong and Guy Hoffman},
journal= {arXiv preprint arXiv:2011.01969},
year = {2020}
}
Comments
In Proceedings of the AAAI 2020 Fall Symposium Series on Trust and Explainability in Artificial Intelligence for Human-Robot Interaction