CHREST is a cognitive architecture that models human perception, learning, memory and problem solving. Its distinctive features include an emphasis on the importance of perception and attention, and the incorporation of human constraints, such as limitations on short-term memory and processing speed. CHREST is particulary suited to modelling human learning in domains involving high-level (symbolic) information.
For the latest information about CHREST, please visit our website: http://chrest.info, sign up to our mailing list, and follow us on twitter @chrest_news.
This tutorial should take approximately 2 hours. The lecture slides may be viewed by clicking on the link in the table below.
Topic | Duration |
---|---|
Introduction to tutorial | 5 minutes |
Overview of CHREST | 10 minutes |
Learning mechanisms | 25 minutes |
Demonstration/practical 1 | 20 minutes |
Key results (expertise) | 20 minutes |
Demonstration/practical 2 | 20 minutes |
Working with your data: Input format, scripting | 15 minutes |
Conclusion | 5 minutes |
We have provided some sample papers to introduce the CHREST literature. Note that some of these are preprints. The latest publications are announced on the mailing list, and posted at http://chrest.info.
Chess has been influential in the psychological study of expertise, ever since the early work of de Groot in 1946 established the importance of the recall experiment.
Recent work with CHREST has looked at adding problem-solving behaviour. This has mostly been limited to chess.
The use of fMRI studies in cognitive science has not had a long history, but some useful experiments have been performed.
The CHREST implementation is in the 'Software' folder of this CDROM. The latest version is available from http://chrest.info/software.html