@inbook{eba39702ace644138e1031ecbea2807f,
title = "A computer mouse-based throwing task to study perceptual-motor skill learning in humans and machines",
abstract = "Perceptual-motor tasks offer redundant solutions to achieve a goal. However, not all solutions are equally robust to error-producing noise or variability and thus, skill learning can be viewed as a search process to identify behaviors that are error-tolerant. Throwing a ball to hit a target is one such example of a complex perceptual-motor skill that has been studied in the laboratory via the virtual “skittles” task, a simplified 2D task involving throwing a tetherball around a pole to hit a target. We implemented the task as a Unity3D environment (code here: https://github.com/ShortFox/SkittlesTaskEnvironment/) which enables participants to complete the task with a computer mouse and replicated key findings from previous research. Our implementation allows for remote data collection and can serve as a pedagogical tool to teach concepts in skill acquisition. Future work will use this task to explore human versus machine skill acquisition by leveraging Unity{\textquoteright}s MLAgents reinforcement learning package.",
author = "Patrick Nalepka and Georgina Schell and Gaurav Patil and Michael Richardson",
note = "Copyright the Author(s) 2022. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.; Annual Meeting of the Cognitive Science Society (44th : 2022), CogSci 2022 ; Conference date: 27-07-2022 Through 30-07-2022",
year = "2022",
language = "English",
series = "Proceedings of the Annual Meeting of the Cognitive Science Society",
publisher = "Cognitive Science Society",
pages = "3770",
editor = "J. Culbertson and A. Perfors and H. Rabagliati and V. Ramenzoni",
booktitle = "CogSci2022",
}