| | --- |
| | license: apache-2.0 |
| | pipeline_tag: reinforcement-learning |
| | datasets: |
| | - cheryyunl/Make-An-Agent |
| | --- |
| | |
| | Pretrained models for Make-An-Agent. See https://github.com/cheryyunl/Make-An-Agent for usage instructions. |
| |
|
| | `autoencoder.pt` and `behavior_embedding.pt` are trained with parameter data and trajectory data in `train_data/data.pt` of our dataset. |
| |
|
| | `model-best.pt` is the policy generator model trained by latent parameter representation data and behavior embedding data in `train_data/process_data.pt` |
| |
|
| | ## 📝 Citation |
| |
|
| | If you find our model or dataset useful, please consider citing as follows: |
| |
|
| | Cite arxiv.org/abs/2407.10973 |
| |
|
| |
|
| | ``` |
| | @article{liang2024make, |
| | title={Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion}, |
| | author={Liang, Yongyuan and Xu, Tingqiang and Hu, Kaizhe and Jiang, Guangqi and Huang, Furong and Xu, Huazhe}, |
| | journal={arXiv preprint arXiv:2407.10973}, |
| | year={2024} |
| | } |
| | ``` |
