understanding helping behaviors

Repository for storing data and analysis scripts for the helping behaviors project

data structure

1. e1 data contains the raw gameplay data from 100 dyads (N = 200)
2. e1 demo contains the demographic information

code structure

1. There are 4 key .py files:

• utils.py contains base functions to create goalspace, compute utilities, etc.
• agents.py contains the functions for the helper and demonstrator/architect models
• process_data.py contains functions to obtain move sequences, ranks, etc. from the raw data
• optimizer.py contains functions to obtain the best-fitting parameter values for different agent models

2. There is also a notebook assistance_demo.ipynb that contains a demonstration of how to look at the data and obtain outputs from different agents/functions.

3. Finally, there is a .Rmd file that contains the analyses based on results obtained from the python files.