TY - GEN
T1 - On the effect of user faults on her perception of agents faults in collaborative settings
AU - Asraf, Reut
AU - Rozenshtein, Chen
AU - Sarne, David
N1 - Publisher Copyright: © 2021 Owner/Author.
PY - 2021/11/9
Y1 - 2021/11/9
N2 - In various human-Agent collaborative settings the agent is fault-prone. In many of these settings, it is possible that the human user will also account to failure, hindering task execution. In this paper we study the effect of the latter type of failures over the user's satisfaction with the agent in the collaborative setting. We report the results of two experiments, differing in the number of agent's faults and the way faults influence task progress and attract players' focus, with 264 subjects recruited and interacted through Amazon Mechanical Turk. We find that when the user accounts for some faults during the collaborative execution of the task, she becomes more forgiving to the agent faults, and consequently more satisfied with the collaboration, compared to the case where she makes no faults. The importance of this finding becomes most apparent in the design of collaborative agents.
AB - In various human-Agent collaborative settings the agent is fault-prone. In many of these settings, it is possible that the human user will also account to failure, hindering task execution. In this paper we study the effect of the latter type of failures over the user's satisfaction with the agent in the collaborative setting. We report the results of two experiments, differing in the number of agent's faults and the way faults influence task progress and attract players' focus, with 264 subjects recruited and interacted through Amazon Mechanical Turk. We find that when the user accounts for some faults during the collaborative execution of the task, she becomes more forgiving to the agent faults, and consequently more satisfied with the collaboration, compared to the case where she makes no faults. The importance of this finding becomes most apparent in the design of collaborative agents.
KW - HAI experimental methods
KW - Human-virtual agent interaction
KW - Intelligent user interfaces
UR - http://www.scopus.com/inward/record.url?scp=85119322523&partnerID=8YFLogxK
U2 - 10.1145/3472307.3484681
DO - 10.1145/3472307.3484681
M3 - منشور من مؤتمر
T3 - HAI 2021 - Proceedings of the 9th International User Modeling, Adaptation and Personalization Human-Agent Interaction
SP - 372
EP - 376
BT - HAI 2021 - Proceedings of the 9th International User Modeling, Adaptation and Personalization Human-Agent Interaction
T2 - 9th International User Modeling, Adaptation and Personalization Human-Agent Interaction, HAI 2021
Y2 - 9 November 2021 through 11 November 2021
ER -