From 062b0a421663e90ef8171c6da849c52e4b16623d Mon Sep 17 00:00:00 2001 From: Alexis Cook Date: Sat, 7 Jul 2018 10:22:22 -0500 Subject: [PATCH] Update README.md --- p1_navigation/README.md | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/p1_navigation/README.md b/p1_navigation/README.md index b814e8f2b..6e44ececf 100644 --- a/p1_navigation/README.md +++ b/p1_navigation/README.md @@ -37,3 +37,19 @@ The task is episodic, and in order to solve the environment, your agent must get ### Instructions Follow the instructions in `Navigation.ipynb` to get started with training your own agent! + +### (Optional) Challenge: Learning from Pixels + +After you have successfully completed the project, if you're looking for an additional challenge, you have come to the right place! In the project, your agent learned from information such as its velocity, along with ray-based perception of objects around its forward direction. A more challenging task would be to learn directly from pixels! + +To solve this harder task, you'll need to download a new Unity environment. This environment is almost identical to the project environment, where the only difference is that the state is an 84 x 84 RGB image, corresponding to the agent's first-person view. (**Note**: Udacity students should not submit a project with this new environment.) + +You need only select the environment that matches your operating system: +- Linux: [click here](https://s3-us-west-1.amazonaws.com/udacity-drlnd/P1/Banana/VisualBanana_Linux.zip) +- Mac OSX: [click here](https://s3-us-west-1.amazonaws.com/udacity-drlnd/P1/Banana/VisualBanana.app.zip) +- Windows (32-bit): [click here](https://s3-us-west-1.amazonaws.com/udacity-drlnd/P1/Banana/VisualBanana_Windows_x86.zip) +- Windows (64-bit): [click here](https://s3-us-west-1.amazonaws.com/udacity-drlnd/P1/Banana/VisualBanana_Windows_x86_64.zip) + +Then, place the file in the `p1_navigation/` folder in the DRLND GitHub repository, and unzip (or decompress) the file. Next, open `Navigation_Pixels.ipynb` and follow the instructions to learn how to use the Python API to control the agent. + +(_For AWS_) If you'd like to train the agent on AWS, you must follow the instructions to [set up X Server](https://github.com/Unity-Technologies/ml-agents/blob/master/docs/Training-on-Amazon-Web-Service.md), and then download the environment for the **Linux** operating system above.