Investigating the role of Imitation and Emulation in Decision Making
psychopy task of the implemented paper
This Project is a Python Implementation of a paper entitled “A Neuro‑computational Account of Arbitration between Choice Imitation and Goal Emulation during Human Observational Learning” by Caroline J. Charpentier et al. Data of participants in the task is provided by the authors. I used this data to Implement the models that are introduced in the paper to investigate the role of Imitation and emulation in our Daily Decision Making.
Results
After Implementing the models of paper, the results are as shown in the table below
| Class | Model | Out of Sample Accuracy% |
|---|---|---|
| Emulation Inference | 1 | 49,62 |
| Emulation Inference | 2 | - |
| Imitation RL | 3 | 51,37 |
| Imitation RL | 4 | 53,88 |
| Emulation RL | 5 | 52,16 |
| Emulation RL | 6 | 52,63 |
| Arbitration | 7 | 54,63 |
| Arbitration | 8 | - |
Due to the results best model is Arbitration model.
Amir Mesbah
Master student in Artificial Intelligence and Robotics
My research interests include Machine Learning.