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.
Original language | English |
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Title of host publication | CHI EA '22 |
Subtitle of host publication | Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems |
Editors | Simone Barbosa, Cliff Lampe, Caroline Appert, David A. Shamma |
Place of Publication | New York |
Publisher | Association for Computing Machinery (ACM) |
Pages | 1-3 |
Number of pages | 3 |
ISBN (Electronic) | 9781450391566 |
DOIs | |
Publication status | Published - 28 Apr 2022 |
Event | CHI '22: CHI Conference on Human Factors in Computing Systems - New Orleans, United States Duration: 29 Apr 2022 → 5 May 2022 |
Publication series
Name | CHI: Conference on Human Factors in Computing Systems |
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Conference
Conference | CHI '22 |
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Country/Territory | United States |
City | New Orleans |
Period | 29/04/22 → 5/05/22 |
Bibliographical note
Publisher Copyright:© 2022 Owner/Author.
Keywords
- cognitive architectures
- Cognitive modeling
- computational rationality
- cooperative intelligence
- deep learning
- reinforcement learning
- user interface optimization
ASJC Scopus subject areas
- Human-Computer Interaction
- Computer Graphics and Computer-Aided Design
- Software