/synergy

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

Primary LanguagePythonMIT LicenseMIT

HumanWareFundemental: Sysngy Team

This repository is cloned from openai/baselines and modifided for our reseach. Don't make PR for ofiginal repogitory.

Train model with DDPG

TBA


Memo

TBA


Initial Setup

Virtual environment

From the general python package sanity perspective, it is a good idea to use virtual environments (virtualenvs) to make sure packages from different projects do not interfere with each other. You can install virtualenv (which is itself a pip package) via

pip install virtualenv

Virtualenvs are essentially folders that have copies of python executable and all python packages. To create a virtualenv called venv with python3, one runs

virtualenv /path/to/venv --python=python3

To activate a virtualenv:

. /path/to/venv/bin/activate

More thorough tutorial on virtualenvs and options can be found here

Installation

  • Clone the repo and cd into it:

    git clone https://github.com/openai/baselines.git
    cd baselines
  • If you don't have TensorFlow installed already, install your favourite flavor of TensorFlow. In most cases,

    pip install tensorflow-gpu # if you have a CUDA-compatible gpu and proper drivers

    or

    pip install tensorflow

    should be sufficient. Refer to TensorFlow installation guide for more details.

  • Install baselines package

    pip install -e .

MuJoCo

Some of the baselines examples use MuJoCo (multi-joint dynamics in contact) physics simulator, which is proprietary and requires binaries and a license (temporary 30-day license can be obtained from www.mujoco.org). Instructions on setting up MuJoCo can be found here