Personalized Agent Explanations for Human-Agent Teamwork: Adapting Explanations to User Trust, Workload, and Performance

Conference paper (2023)

Authors

R.S. Verhagen Interactive Intelligence - EEMCS
M.A. Neerincx Interactive Intelligence - EEMCS
C. Parlar Student
M. Vogel Student
M.L. Tielman Interactive Intelligence - EEMCS
Research Group
Interactive Intelligence (EEMCS) (TU Delft)
Copyright: © 2023 R.S. Verhagen, M.A. Neerincx, C. Parlar, M. Vogel, M.L. Tielman
More Info
expand_more

Published Date

2023

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Intelligent Systems

Research Group

Interactive Intelligence

Abstract

For human-agent teams to be successful, agent explanations are crucial. These explanations should ideally be personalized by adapting them to intended human users. So far, little work has been conducted on personalized agent explanations during human-agent teamwork. Therefore, an online experiment (n = 60) was conducted to compare personalized agent explanations against a baseline of non-personalized explanations. We implemented four agents who adapted their explanations during a search and rescue task randomly, or based on human workload, performance, or trust. Results show that personalized explanations can increase explanation satisfaction and trust in the agent, but also decrease performance. Therefore, we conclude that personalized agent explanations can be beneficial to human-agent teamwork, but that user modelling and personalization techniques should be carefully considered.