diff --git a/units/en/unit3/hands-on.mdx b/units/en/unit3/hands-on.mdx index f0a7d4e..8c8080a 100644 --- a/units/en/unit3/hands-on.mdx +++ b/units/en/unit3/hands-on.mdx @@ -38,7 +38,7 @@ And you can check your progress here 👉 https://huggingface.co/spaces/ThomasSi Unit 3 Thumbnail -In this notebook, **you'll train a Deep Q-Learning agent** playing Space Invaders using [RL Baselines3 Zoo](https://github.com/DLR-RM/rl-baselines3-zoo), a training framework based on [Stable-Baselines3](https://stable-baselines3.readthedocs.io/en/master/) that provides scripts for training, evaluating agents, tuning arameters, plotting results and recording videos. +In this notebook, **you'll train a Deep Q-Learning agent** playing Space Invaders using [RL Baselines3 Zoo](https://github.com/DLR-RM/rl-baselines3-zoo), a training framework based on [Stable-Baselines3](https://stable-baselines3.readthedocs.io/en/master/) that provides scripts for training, evaluating agents, tuning parameters, plotting results and recording videos. We're using the [RL-Baselines-3 Zoo integration, a vanilla version of Deep Q-Learning](https://stable-baselines3.readthedocs.io/en/master/modules/dqn.html) with no extensions such as Double-DQN, Dueling-DQN, and Prioritized Experience Replay.