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Exploring multitasking strategies in an ACT-R model of a complex piloting task

Garrett Swan
Aptima, Inc.
Christopher Adam Stevens
Air Force Research Laboratory
Dr. Christopher Fisher
Parallax Advanced Research
Samantha Klosterman

Multitasking is a challenging cognitive task, and there are many factors driving which strategy participants use to complete tasks concurrently. We utilized a model comparison approach to evaluate how participants decide which task to switch to next using the Air Force Multiple Attribute Battery (AF-MATB). We used the cognitive architecture, Adaptive Control of Thought – Rational (ACT-R), to simulate multitasking in the AF-MATB. We varied how the model decided which task to attend to next by comparing a purely top-down strategy, a purely reactive, bottom-up selection strategy, and mixtures of the two. We compared simulations of the model to data from Bowers et al., (2014). The best combination involved a mixture of top-down and bottom-up selection. Neither the purely top-down nor bottom-up selection models performed well. These results suggest that participants use a complex mixture of strategies to multitasking. The use of a top-down strategy suggests participants could develop efficient strategies to multitask successfully, and that participants may be using a more effortful serial search for tasks, as indicated by the model's serial processing implementation.



cognitive architecture
Strategy Switching Last updated 1 year ago

Great presentation Garrett. Here is some possibly relevant research on identifying strategy switching during multi-tasking.

Dr. Edward Cranford 1 comment
Could the organizer let people in? Last updated 1 year ago

please let people in the session.

Prof. Cleotilde (Coty) Gonzalez 0 comments
Cite this as:

Swan, G., Stevens, C., Fisher, C. R., & Klosterman, S. (2022, July). Exploring multitasking strategies in an ACT-R model of a complex piloting task. Paper presented at Virtual MathPsych/ICCM 2022. Via