Python implementation of the Linear Reinforcement Learning model introduced by Piray and Daw (2021)

A toolset for evaluating the results and impacts of an educational event, employing cognitive maps as a model for representing cognitive structures or knowledge.

Cognitive map for predicting univariate time-series using ADAM optimization. Coded from scratch without any help of machine learning libraries.

Open-source code repository where reinforcement learning agents solve grid-maze environment and represent learning process as a graph learning.

Cognitive maps as excel files

Documentation for the Python cityImage package