Cognitive Modeling: From GOMS to Deep Reinforcement Learning

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

Research output: Contribution to conferencePaperScientificpeer-review


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.

Original languageEnglish
Number of pages2
Publication statusPublished - 11 May 2024
MoE publication typeNot Eligible
EventACM SIGCHI Annual Conference on Human Factors in Computing Systems - Honolulu, USA, Honolulu, United States
Duration: 11 May 202416 May 2024


ConferenceACM SIGCHI Annual Conference on Human Factors in Computing Systems
Abbreviated titleACM CHI
Country/TerritoryUnited States
Internet address


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


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