In this environment, two agents control rackets to bounce a ball over a net. If an agent hits the ball over the net, it receives a reward of +0.1. If an agent lets a ball hit the ground or hits the ball out of bounds, it receives a reward of -0.01. Thus, the goal of each agent is to keep the ball in play.

The observation space consists of 8 variables corresponding to the position and velocity of the ball and racket. Each agent receives its own, local observation. Two continuous actions are available, corresponding to movement toward (or away from) the net, and jumping.

The environment is considered solved, when the average (over 100 episodes) of those scores is at least +0.5. The agents in the gif above was able to score +0.8.

Step 1:

git clone https://github.com/zhuohann/MADDPG

Step 2:

Use the package manager pip.

pip install -r requirements.txt

Step 3:

Download the Unity environment:

• Linux
• Mac OSX
• Windows (32-bit)
• Windows (64-bit)

The agents were able to reach an average score of ,over 100 consecutive episodes,0.5 after just 552 episodes.

Run Tennis.ipynb

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

MIT