Python package to create and run ACT-R cognitive models.
The package supports symbolic and subsymbolic processes in ACT-R and it covers all basic cases of ACT-R modeling, including features that are not often implemented outside of the official Lisp ACT-R software.
The package should allow you to run any ACT-R model. If you need an ACT-R feature that's missing in the package, please open an issue.
Significant changes might still occur in the near future.
The best way to install pyactr is to run pip:
pip3 install pyactrYou can also clone this package and in the root folder, and run:
python setup.py installpyactr requires Python3 (>=3.3), numpy, simpy, and pyparsing.
You might also consider getting tkinter if you want to see visual output on how ACT-R models interact with environment. But this is not necessary to run any models.
pyactr works with Python 3.3 but some packages that it is dependent on dropped support for Python 3.3. If you want to use pyactr with Python 3.3 you must install numpy version 1.11.3 or lower. simpy is also planning to drop support of Python 3.3 in future versions (as of January 2019).
A short introduction to ACT-R and pyactr may be found in the wiki.
There is a book published recently by Springer that uses pyactr. The book is geared towards (psycho)linguists but it includes a lot of code that can be useful to cognitive scientists outside of psycholinguistics. It explains how models can be created and run in pyactr, from simple counting models up to complex psychology models (fan effects, interpretation of complex sentences).
Computational Cognitive Modeling and Linguistic Theory is open access and available here.
Some more documents may be found in the GitHub repository. In particular, check the folder tutorials for many examples of ACT-R models. Most of those models are translated from Lisp ACT-R, so if you are familiar with Lisp ACT-R they should be fairly easy to understand.
To ensure that modifications do not break the current code, run unit tests in pyactr/tests/.
python -m unittest