The project is to train an agent to navigate and collect bananas in a large, square world.
A reward of +1 is provided for collecting a yellow banana, and a reward of -1 is provided for collecting a blue banana. Thus, the goal of the agent is to collect as many yellow bananas as possible while avoiding blue bananas.
There are two versions of the state space: nonpixel and pixel. The nonpixel state has 37 dimensions and contains the agent's velocity, along with ray-based perception of objects around agent's forward direction. The pixel state is an 84 x 84 RGB image, corresponding to the agent's first-person view of the environment.
Four discrete actions are available, corresponding to:
0
- move forward.1
- move backward.2
- turn left.3
- turn right.
The task is episodic, and in order to solve the environment, the agent must get an average score of +13 over 100 consecutive episodes.
First set up the virtual environment and install dependencies in requirements.txt. To create a virtual environment, decide upon a directory where you want to place it, and run the venv module as a script with the directory path:
python3 -m venv <path to the target directory>
Once you’ve created a virtual environment, you may activate it.
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On Windows, run:
\<path to the target directory>\Scripts\activate.bat
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On Unix or MacOS, run:
source <path to the target directory>/bin/activate
(This script is written for the bash shell. If you use the csh or fish shells, there are alternate activate.csh and activate.fish scripts you should use instead.)
After activating the environment, install the dependencies from requirements.txt by running:
pip install -r requirements.txt
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Download the environment from one of the links below. You need only select the environment that matches your operating system:
- Linux: click here
- Mac OSX: click here
- Windows (32-bit): click here
- Windows (64-bit): click here
(For Windows users) Check out this link if you need help with determining if your computer is running a 32-bit version or 64-bit version of the Windows operating system.
(For AWS) If you'd like to train the agent on AWS (and have not enabled a virtual screen), then please use this link to obtain the environment.
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Place the file into the
p1_navigation
folder, and unzip (or decompress) the file. -
Open
main.ipynb
and follow the instructions to train the agent.
- Download the environment from one of the links below. You need only select the environment that matches your operating system:
- Linux: click here
- Mac OSX: click here
- Windows (32-bit): click here
- Windows (64-bit): click here (For AWS) If you'd like to train the agent on AWS, you must follow the instructions to set up X Server, and then download the environment for the Linux operating system above.
-
Place the file into the
p1_navigation
folder, and unzip (or decompress) the file. -
Open
main_visual.ipynb
and follow the instructions to train the agent.