File size: 4,507 Bytes
6be2395 fcca4b3 6be2395 fcca4b3 6be2395 fcca4b3 9d3ecaa fcca4b3 1a0f841 fcca4b3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 |
---
annotations_creators: []
language:
- code
license: cc-by-4.0
pretty_name: KoopmanRL
size_categories:
- unknown
source_datasets: []
task_categories:
- reinforcement-learning
task_ids: []
---
# Dataset Card for KoopmanRL
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Dataset Structure](#dataset-structure)
- [Reproducing Plots](#reproducing-plots)
- [Usage of the Dataset](#usage-of-the-dataset)
- [Licensing](#licensing)
- [Contact Info](#contact-info)
- [How to Cite](#how-to-cite)
## Dataset Description
- **Homepage:** https://dynamicslab.github.io/KoopmanRL-NeurIPS/
- **Paper:** https://arxiv.org
- **Leaderboard:** N/A
## Dataset Summary
This dataset contains the collected experimental data used for the results of _Koopman-Assisted Reinforcement Learning_ allowing for the full reproduction, and further use of the paper's results. To reproduce the results by running the experiments yourself, please see the [source code](https://github.com/Pdbz199/Koopman-RL) of KoopmanRL.
## Dataset Structure
The dataset of the reinforcement learning experiments for KoopmanRL contains roughly 461MB of Tensorboard files, and saved policies.
| Experiment | Size | Purpose |
|------------|------|---------|
| Episodic Returns | 161MB | Episodic returns of all 5 considered algorithms across all 4 environments |
| Interpretability | 55MB | Inspection of the interpretability introduced by KoopmanRL |
| AblationSKVIBatchSize | 3.4MB | Ablation of the sensitivity to the chosen batch size |
| AblationSKVICompute | 21MB | Ablation of the sensitivity to the amount of compute used for the construction of the Koopman tensor |
| AblationSAKCMonoid | 86MB | Ablation of the sensitivity to the order of the monoids used for the construction of the dictionaries of the Koopman tensor |
| AblationSAKCCompute | 134MB | Ablation of the sensitivity to the amount of compute used for the construction of the Koopman tensor |
In addition the already extracted dataframes are provided. All experiments are stored as Tensorboard files, with the extracted episodic returns stores in `.parquet.gz` data frames for use with [Pandas](https://pandas.pydata.org/docs/index.html), and saved policies stored in `.pt` files.
## Reproducing Plots
All plots can be reproduced with the respective Jupyter notebooks, which can be found in the order of appearance in the paper:
* [Episodic Returns](https://github.com/ludgerpaehler/KoopmanRLBenchmarking/blob/master/evaluations/episodic_returns.ipynb)
* [Zoomed-in Episodic Returns of the Fluid Flow and Double Well](https://github.com/ludgerpaehler/KoopmanRLBenchmarking/blob/master/evaluations/zoomed_in.ipynb)
* [Zoomed-in Episodic Returns of the Linear System](https://github.com/ludgerpaehler/KoopmanRLBenchmarking/blob/master/evaluations/zoomedin_linear.ipynb)
* [Interpretability Plots & Numbers](https://github.com/ludgerpaehler/KoopmanRLBenchmarking/blob/master/evaluations/interpretability.ipynb)
* [Ablation Heatmaps](https://github.com/ludgerpaehler/KoopmanRLBenchmarking/blob/master/evaluations/ablation_heatmaps.ipynb)
## Usage of the Dataset
The dataset can easiest be used with the [HuggingFace Datasets Library](https://huggingface.co/docs/datasets/index), with which one is able to either download the entire dataset
```python
from datasets import load_dataset
ds = load_dataset("dynamicslab/KoopmanRL")
```
or a desired subparts of the dataset
```python
from datasets import load_dataset
ds = load_dataset("dynamicslab/KoopmanRL", data_dir="data/EpisodicReturns")
```
## Licensing
The entire dataset is licensed under a [CC-BY-4.0 license](https://spdx.org/licenses/CC-BY-4.0.html).
## Contact Info
1. Preston Rozwood (pwr36@cornell.com)
2. Edward Mehrez (ejm322@cornell.edu)
3. Ludger Paehler (paehlerludger@gmail.com)
4. Steven L. Brunton (sbrunton@uw.edu)
## How to Cite
Please cite the dataset in the following format
```bibtex
@misc{dynamicslab_2024,
author={ {Dynamicslab} },
title={ KoopmanRL (Revision fcca4b3) },
year=2024,
url={ https://huggingface.co/datasets/dynamicslab/KoopmanRL },
doi={ 10.57967/hf/1825 },
publisher={ Hugging Face }
}
```
alongside the paper
```bibtex
@article{rozwood2024koopman,
title={Koopman-Assisted Reinforcement Learning},
author={Rozwood, Preston and Mehrez, Edward and Paehler, Ludger and Sun, Wen and Brunton, Steven L.},
journal={arXiv preprint arXiv:tbd},
year={2024}
}
```
|