Cognitive Modelling: From GOMS to Deep Reinforcement Learning

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

Research output: Contribution to conferenceAbstractScientificpeer-review

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 languageEnglish
Pages1-3
Number of pages3
DOIs
Publication statusPublished - 19 Apr 2023
MoE publication typeNot Eligible
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Hamburg, Germany
Duration: 23 Apr 202328 Apr 2023
https://chi2023.acm.org/

Conference

ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleACM CHI
Country/TerritoryGermany
CityHamburg
Period23/04/202328/04/2023
Internet address

Keywords

  • cognitive architectures
  • Cognitive modeling
  • computational rationality
  • cooperative intelligence
  • deep learning
  • reinforcement learning
  • user interface optimization

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