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Code for CHAROT: Robustly controlling chaotic PDEs with partial observations

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Overview

This repository contains the source code accompanying the paper

CHAROT: Robustly controlling chaotic PDEs with partial observations

Accepted at the ICLR 2024 Workshop on AI4Differential Equations in Science.

How to run

First install the requirements by running pip install -r requirements.txt. (If you are running on MacOS with an M1 chip, you need to install torchrl 0.2.0 from the GitHub repo.)

To run a training script, simply run python tqc.py.

All relevant hyperparameters may be changed in 'config.yaml'. In particular, to select which augmentation of TQC should be run, change the network.architecture parameter to one of 'base', 'attention' (= CHAROT) or 'lstm'.

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Code for CHAROT: Robustly controlling chaotic PDEs with partial observations

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