Flow
介绍 Introduction
Flow: A deep reinforcement learning framework for mixed autonomy traffic developed by UC Berkeley.
lnk:https://flow-project.github.io/
UC Berkeley is the best university for traffic engineer students. — He Zhengbing
安装 Installation
简述一下自己的安装过程：分别在Ubuntu18的虚拟机和Macbook Pro M1都配置了Flow。其中Ubuntu18的Flow可以进行强化学习训练，M1 Mac因为ARM架构无法运行ray.rllib（Flow所支持的强化学习框架之一）
自己参考官方文档，大约摸索了一晚上，配置成功。
lnk:https://flow.readthedocs.io/en/latest/flow_setup.html
Next >>> Flow01 Installation
为进一步了解SUMO以及Flow可以参考的文档及文献。
Pulications lnk:
https://flow-project.github.io/publications.html
“Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control”, C. Wu, A. Kreidieh, K. Parvate, E. Vinitsky, A. Bayen, arXiv preprint arXiv:1710.05465, 2017
When citing Flow, please cite this paper
“Benchmarks for reinforcement learning in mixed-autonomy traffic”, E. Vinitsky, A. Kreidieh, L. Flem, N. Kheterpal, K. Jang, C. Wu, F. Wu, R. Liaw, E. Liang, A. Bayen, PMLR, Volume 87, 2018
> When citing the benchmarks, please cite this paper
Tutorial lnk:
https://flow-project.github.io/tutorial.html
之后会根据Tutorials的内容来更新博客！