This repository contains our group project for the course, "Modeling in Cognitive Science" by Prof. Dr. Sebastian Musslick at the University Osnabrück.
In this project, we implement model-free, model-based and hybrid reinforcement learning agents train on the two-step task by Daw. et al (2011) (https://doi.org/10.1016/j.neuron.2011.02.027).
The full pipeline can be found and run in the final submission notebook, https://github.com/imtezcan/rl-twoStepTask/blob/main/hybrid_rl_modeling-TST.ipynb
Additionally, separate code pieces are provided. RL agent implementations can be found under the agents/ folder. Parameter fitting, parameter recovery and model recovery code, as well as the code for analysis are under the root folder.
Authors:
- Ibrahim Muhip Tezcan (itezcan@uos.de)
- Se Eun Choi (seechoi@uni-osnabrueck.de)
- Andrei Klimenok (aklimenok@uni-osnabrueck.de)
- Mohamad Aljammal (maljammal@uni-osnabrueck.de)
- Therese Mayr (tmayr@uni-osnabrueck.de)
- Eray Sevük (esevuek@uni-osnabrueck.de)