Twin Delayed Deep Deterministic Policy Gradient

Trained Agent - Ant

Trained Agent - Humanoid

Trained Agent - Walker

Trained Agent - HalfCheetah

The Theoretical Background

My Notes: click here

The paper: click here

Getting Started

1. Create (and activate) a new environment with Python 3.6.

conda create --name env_name python=3.6
source activate env_name

2. Install Sourcecode dependencies

conda install pytorch torchvision cudatoolkit=9.0 -c pytorch
pip install gym
pip install pybullet
sudo apt-get install ffmpeg

3. Run the Code

How to run the project

You can run the project by running the main.py file through the console.

• open the console and run: python main.py -c "your_config_file.json"
• to train the agent from scratch set "run_training" in the config file to true
• to run the pre-trained agent set "run_training" in the config file to false

optional arguments:

-h, --help

- show help message

-c , --config

- Config file name - file must be available as .json in ./configs

Example: python main.py -c "AntBulletEnv_v0.json"