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 ([email protected])
- Se Eun Choi ([email protected])
- Andrei Klimenok ([email protected])
- Mohamad Aljammal ([email protected])
- Therese Mayr ([email protected])
- Eray Sevük ([email protected])