Clustering Trust Dynamics in a Human-Robot Sequential Decision-Making Task

Autor:	Bhat, Shreyas, Lyons, Joseph B., Shi, Cong, Yang, X. Jessie
Rok vydání:	2022
Předmět:	Computer Science - Robotics Computer Science - Human-Computer Interaction
Druh dokumentu:	Working Paper
Popis:	In this paper, we present a framework for trust-aware sequential decision-making in a human-robot team. We model the problem as a finite-horizon Markov Decision Process with a reward-based performance metric, allowing the robotic agent to make trust-aware recommendations. Results of a human-subject experiment show that the proposed trust update model is able to accurately capture the human agent's moment-to-moment trust changes. Moreover, we cluster the participants' trust dynamics into three categories, namely, Bayesian decision makers, oscillators, and disbelievers, and identify personal characteristics that could be used to predict which type of trust dynamics a person will belong to. We find that the disbelievers are less extroverted, less agreeable, and have lower expectations toward the robotic agent, compared to the Bayesian decision makers and oscillators. The oscillators are significantly more frustrated than the Bayesian decision makers. Comment: 4 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2206.01645 Zobrazit plný text záznamu View this record from Arxiv