Cognitive modeling

From GOMS to Deep Reinforcement Learning 

CHI 2023 Onsite Course, April 26

Course highlights

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.

Course contents

The course consists of four 90 minute modules. All modules make use of Python Notebooks, which are found at the public repository https://github.com/howesa/CHI22-CogMod-Tutorial (please see the repository documentation for installation instructions).

Schedule and Registration

The course fills one conference day (from early morning to late afternoon), and is only available on-site at Hamburg.

April 26. 9:00-18:00


Instructors

Jussi P.P. Jokinen

Assistant Professor, Cognitive Science

University of Jyväskylä

https://www.jyu.fi/it/fi/tiedekunta/henkilosto/henkilosto/jokinen-jussi

Antti Oulasvirta

Professor, Computer Science

Aalto University

http://users.comnet.aalto.fi/oulasvir/

Andrew Howes