course

Cognitive Modelling: From GOMS to Deep Reinforcement Learning

Authors:

Jussi P. P. Jokinen,

Antti Oulasvirta,

Andrew HowesAuthors Info & Claims

CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Article No.: 533, Pages 1 - 3

https://doi.org/10.1145/3544549.3574173

Published: 19 April 2023 Publication History

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Abstract

This course introduces computational cognitive modeling for researchers and practitioners in the field of HCI. Cognitive models use computer programs to model how users perceive, think, and act in human–computer interaction. They offer a powerful approach for understanding interactive tasks and improving user interfaces. This course starts with a review of classic architecture based models such as GOMS and ACT-R. It then rapidly progresses to introducing modern modelling approaches powered by machine learning methods, in particular deep learning, reinforcement learning (RL), and deep RL. The course is built around hands-on Python programming using notebooks.

References

[1]

Noshaba Cheema, Laura A Frey-Law, Kourosh Naderi, Jaakko Lehtinen, Philipp Slusallek, and Perttu Hämäläinen. 2020. Predicting mid-air interaction movements and fatigue using deep reinforcement learning. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1–13.

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[2]

Xiuli Chen, Aditya Acharya, Antti Oulasvirta, and Andrew Howes. 2021. An adaptive model of gaze-based selection. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–11.

Digital Library

Google Scholar

[3]

Jussi PP Jokinen, Aditya Acharya, Mohammad Uzair, Xinhui Jiang, and Antti Oulasvirta. 2021. Touchscreen typing as optimal supervisory control. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems. 1–14.

Digital Library

Google Scholar

[4]

Jussi PP Jokinen, Tuomo Kujala, and Antti Oulasvirta. 2020. Multitasking in driving as optimal adaptation under uncertainty. Human Factors (2020), 18. https://doi.org/10.1177/0018720820927687

Crossref

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[5]

Antti Oulasvirta, Jussi PP Jokinen, and Andrew Howes. 2022. Computational Rationality as a Theory of Interaction. In CHI Conference on Human Factors in Computing Systems. 1–14.

Digital Library

Google Scholar

[6]

Arianna Yuan and Yang Li. 2020. Modeling human visual search performance on realistic webpages using analytical and deep learning methods. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. 1–12.

Digital Library

Google Scholar

Index Terms

Cognitive Modelling: From GOMS to Deep Reinforcement Learning
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. HCI theory, concepts and models
    2. Interactive systems and tools
      1. User interface programming

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Published In

CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

April 2023

3914 pages

ISBN:9781450394222

DOI:10.1145/3544549

Editors:
Albrecht Schmidt
LMU Munich, Germany
,
Kaisa Väänänen
Tampere University, Finland
,
Tesh Goyal
Google Research, USA
,
Per Ola Kristensson
University of Cambridge, UK
,
Anicia Peters
University of Namibia, Namibia

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 April 2023

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Refereed limited

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Academy of Finland

Conference

CHI '23

Sponsor:

SIGCHI

CHI '23: CHI Conference on Human Factors in Computing Systems

April 23 - 28, 2023

Hamburg, Germany

Acceptance Rates

Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

Upcoming Conference

CHI 2025

Sponsor:
sigchi

ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

Yokohama , Japan

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