Bezos：轻量小巧的深度强化学习框架

Bezos：轻量小巧的深度强化学习框架

Bezos is a light Deep RL framework that you can fork and extend. Report Bug · Request Feature

Table of Contents

Table of ContentsAbout The ProjectFeaturesBuilt With Getting StartedInstallation UsageTrain a model (params in the config file)Evaluate a model ContributingLicenseContact

About The Project

There are many great reinforcement learning frameworks on GitHub, however, I didn't find one that was light and small enough to let me fork it and add my own algorithms while still feeling in control. I thus created Bezos, a very light RL framework which implements all the boring things so that you don't have to.

Features

Rollout class (supports GAE, reward to go, and recurrent neural network)Runner class: loads a Gym env and runs one or multiple agents on the environment to generate rolloutsA simple Actor Critic NetworkRL Algorithm: PPO Paper on ArxivRL Algorithm: A2C OpenAI blog postSupports all the OpenAI Gym envI added all the Vizdoom envs as well (look into kits/)Supports the marLo env Github (look into kits/)A bunch of useful OpenAI Gym wrappers. Includes frame skipping, RGB→Grayscale, cropping, and many more. (look into envs.py)

Built With

The framework uses Pytorch to do all the deep learning stuff, numpy, and OpenAI Gym

PytorchOpenAI GymNumpy

Getting Started

Bezos has been designed to be configured before each run with a YAML file. Some examples of those YAML config files can be found in the configs folder. If you want to know what a parameter does (they are all self explanatory) check the source :)

Installation

Create a new conda env (yo don't use python 2 ok)pip install -r requirements.txt

Usage

Train a model (params in the config file)

python bezos.py --config ./configs/ppo-minecraft.yaml train

Evaluate a model

python bezos.py --config ./configs/ppo-minecraft.yaml evaluate --det

Contributing

Contributions are what make the open source community such an amazing place to be learn, inspire, and create. Any contributions you make are greatly appreciated.

Fork the ProjectCreate your Feature Branch (git checkout -b feature/AmazingFeature)Commit your Changes (git commit -m 'Add some AmazingFeature)Push to the Branch (git push origin feature/AmazingFeature)Open a Pull Request

License

Distributed under the MIT License. See LICENSE for more information.

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