To compute the bonus payments for the participants, run the following notebook:compute_compensation.ipynb
To download the data from the database run the following notebook: save_data.ipynb
To process the data, run the following notebook: process.ipynb
To add the alignment between human and machine actions, run the following notebook: algorithm/compute_alignment.ipynb
To create the visualizations of the experimental data, run the following notebook: visualize.ipynb
This will generate the following figures:
- Figure 3: Four prototypical populations figure 3
- Figure 4: Evolution of Task Performance, Machine Alignment, and Strategy Descrip- tion figure 4
- Supplementary Figure 8 sup fig
- Supplementary Figure 9 sup fig
- Supplementary Figure 10 sup fig
To run the agent-based model, run the following notebook: abm.ipynbb
This notebook will run the agent-based model and generate the following figures:
To compute the learning curve of the algorithm (figure 6), run the following notebook: plot_learning_curve.ipynb
This will generate the following figure:
- Figure 6: Learning Curve of the Algorithm figure 6