Modeling the mind of a predator: Interactive cognitive maps support flexible avoidance of dynamic threats
This repository contains all code necessary to reproduce the analyses from our work on flexible avoidance of dynamic threats.
Data is available from the corresponding OSF repository: https://osf.io/fwgqa/
The /notebooks directory contains Jupyter notebooks that run through all the main analyses, including code to produce the figures in the paper. Some model fitting is run in separate scripts as it makes it easier to run multiple fits in parallel. This is described in more detail in the relevant notebooks.
The code for much of the model fitting is provided in the /code directory. This provides high-level scripts to run the fitting procedures, the use of which is described in the relevant notebooks.
Aside from common Python dependencies for data manipulation and processing (e.g., Numpy, Pandas), this code relies upon the Multi-Agent MDP package (https://github.com/tobywise/multi_agent_mdp).
In addition, the hypothesis testing inverse reinforcement learning model depends on Jax and Numpyro, which do not work on Windows.