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

Conference Paper (2023)
Authors

Ruben Verhagen (TU Delft - Interactive Intelligence)

Mark A. Neerincx (TU Delft - Interactive Intelligence)

C. Parlar (Student TU Delft)

M. Vogel (Student TU Delft)

M.L. Tielman (TU Delft - Interactive Intelligence)

Research Group
Interactive Intelligence
Copyright
© 2023 R.S. Verhagen, M.A. Neerincx, C. Parlar, M. Vogel, M.L. Tielman
More Info
expand_more
Publication Year
2023
Language
English
Copyright
© 2023 R.S. Verhagen, M.A. Neerincx, C. Parlar, M. Vogel, M.L. Tielman
Research Group
Interactive Intelligence
Pages (from-to)
2316–2318
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.

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.

Files

Ex0810_verhagen.pdf
(pdf | 0.619 Mb)
Unspecified
3545946.3598919.pdf
(pdf | 1.11 Mb)
- Embargo expired in 01-01-2024
License info not available