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Cognitive Modelling : From GOMS to Deep Reinforcement Learning

Year of publication

2022

Authors

Jokinen, Jussi P. P.; Oulasvirta, Antti; Howes, Andrew

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.
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Organizations and authors

Aalto University

Howes Andrew

Oulasvirta Antti Orcid -palvelun logo

Publication type

Publication format

Abstract

Parent publication type

Conference

Audience

Scientific

Publication channel information

Conference

Extended abstracts on human factors in computing systems

Publisher

ACM

Article number

121

Open access

Open access in the publisher’s service

No

Self-archived

No

Other information

Fields of science

Computer and information sciences

Keywords

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Publication country

United States

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

No

DOI

10.1145/3491101.3503771

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes