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PyNav

Code used to perform the experiments in the paper "Clock-state olfactory search in turbulent flows using Q-learning: The geometry of plume recovery". Experiment scripts are provided in the experiments folder.

Instructions for setting up the environment and installing dependencies are provided below.

📦 Installation

To use this library, you need to install it. We recommend creating a new Conda environment to manage dependencies.

In particular, this library supports Python >= 3.9 and all experiments were performed using Python 3.10. You can create and activate a Conda environment as follows:

conda create -n pynav python=3.10
conda activate pynav

Then, clone this repository

git clone https://github.com/PimLb/pynav.git
cd pynav

Finally, install the library using the setup.py file

pip install .

The experiments were run using Python 3.10.13 and NumPy 1.26.

The code used to reproduce the POMDP experiments is available at http://github.com/rheinonen/OlfactorySearch/tree/qlearning.

📊 Dataset

The dataset used to perform the experiments can be downloaded from Zenodo at the following link: https://zenodo.org/records/20001730

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Q-learning for Olfactory Navigation

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