Awesome
Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services
This repository is an implementation of the system design and the proposed Deep Diffusion Soft Actor-Critic (D2SAC) algorithm presented in:
"Diffusion-based Reinforcement Learning for Edge-enabled AI-Generated Content Services"
Authored by Hongyang Du, Zonghang Li, Dusit Niyato, Jiawen Kang, Zehui Xiong, Huawei Huang, and Shiwen Mao.
The paper can be found at ArXiv.
Please see <code>docker/Dockerfile</code> for running this project on Docker or use the prebuilt Docker image <code>lizonghango00o1/agod:cpu</code> from Dockerhub directly. Then, run <code>python main.py</code>.
If our code is useful to you, please cite:
Citation
@article{du2024diffusion,
title={Diffusion-based Reinforcement Learning for Edge-enabled {AI}-Generated Content Services},
author={Du, Hongyang and Li, Zonghang and Niyato, Dusit and Kang, Jiawen and Xiong, Zehui and Huang, Huawei and Mao, Shiwen},
journal={IEEE Transactions on Mobile Computing},
year={2024},
publisher={IEEE}
}