Reinforcement learning on a chemoatic cell

On the integration of spatial and temporal information

This repository contains the code used on the paper "Learning optimal integration of spatial and temporal information in noisy chemotaxis"

File Structure

The project is organized as follows:

├── README.md 
├── chemoxrl/ # Folder containing the code related to training the agents and env.
├── chemoxrl_aux/ # Utils functions used in analysis but not needed for training
├── models/ # Trained agents weights.
├── pyproject.toml  # Package setup for both chemoxrl and chemoxrl[aux]
├── requirements.txt # Project dependencies
└── train.py # Script to train the agent.

Setup

Create a virtual environment and install the requiered packages (Note: we use jaxlib for GPU)

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Likewise, we recommend to install this library locally

pip install -e .

Usage

One can train the agent by using

python3 train.py

The available options can be seen by using

python3 train.py --help