course

Cognitive Modeling: From GOMS to Deep Reinforcement Learning

Authors:

Jussi P. P. Jokinen,

Antti Oulasvirta,

Andrew HowesAuthors Info & Claims

CHI EA '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

Article No.: 594, Pages 1 - 2

https://doi.org/10.1145/3613905.3636278

Published: 11 May 2024 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 modeling approaches powered by machine learning methods, in particular deep reinforcement learning. The course is built around hands-on Python programming using notebooks.

References

[1]

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.

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[2]

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.

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[3]

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

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[4]

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.

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Index Terms

Cognitive Modeling: 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 '24: Extended Abstracts of the CHI Conference on Human Factors in Computing Systems

May 2024

4761 pages

ISBN:9798400703317

DOI:10.1145/3613905

Editors:
Florian Floyd Mueller
Monash University
,
Penny Kyburz
The Australian National University
,
Julie R. Williamson
University of Glasgow
,
Corina Sas
Lancaster University

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.

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Association for Computing Machinery

New York, NY, United States

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Published: 11 May 2024

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CHI '24

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CHI '24: CHI Conference on Human Factors in Computing Systems

May 11 - 16, 2024

HI, Honolulu, USA

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

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CHI 2025

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ACM CHI Conference on Human Factors in Computing Systems

April 26 - May 1, 2025

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Abstract

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Recommendations

Cognitive Modelling: From GOMS to Deep Reinforcement Learning

Cognitive Modelling: From GOMS to Deep Reinforcement Learning

Modeling Human Actions in the Cart-Pole Game Using Cognitive and Deep Reinforcement Learning Approach

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