Supporting Task Switching with Reinforcement Learning
Loading...
Access rights
openAccess
URL
Journal Title
Journal ISSN
Volume Title
A4 Artikkeli konferenssijulkaisussa
This publication is imported from Aalto University research portal.
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
View publication in the Research portal (opens in new window)
View/Open full text file from the Research portal (opens in new window)
Other link related to publication (opens in new window)
Date
2024-05-11
Major/Subject
Mcode
Degree programme
Language
en
Pages
18
Series
Conference on Human Factors in Computing Systems - Proceedings
Abstract
Attention management systems aim to mitigate the negative effects of multitasking. However, sophisticated real-time attention management is yet to be developed. We present a novel concept for attention management with reinforcement learning that automatically switches tasks. The system was trained with a user model based on principles of computational rationality. Due to this user model, the system derives a policy that schedules task switches by considering human constraints such as visual limitations and reaction times. We evaluated its capabilities in a challenging dual-task balancing game. Our results confirm our main hypothesis that an attention management system based on reinforcement learning can significantly improve human performance, compared to humans' self-determined interruption strategy. The system raised the frequency and difficulty of task switches compared to the users while still yielding a lower subjective workload. We conclude by arguing that the concept can be applied to a great variety of multitasking settings.Description
Publisher Copyright: © 2024 Copyright held by the owner/author(s)
Keywords
Artifact or System, Interruption, Lab Study, Machine Learning, Notification, Quantitative Methods, Task Switching
Other note
Citation
Lingler, A, Talypova, D, Jokinen, J P P, Oulasvirta, A & Wintersberger, P 2024, Supporting Task Switching with Reinforcement Learning . in CHI 2024 - Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems ., 82, Conference on Human Factors in Computing Systems - Proceedings, ACM, ACM SIGCHI Annual Conference on Human Factors in Computing Systems, Honolulu, Hawaii, United States, 11/05/2024 . https://doi.org/10.1145/3613904.3642063