🐍 Python 3.10 is recommended. Other versions may work but have not been tested.
You also need to install ffmpeg and have it available in the command line.
- Copy your legally obtained Pokemon Red ROM into the base directory. You can find this using google, it should be 1MB. Rename it to
PokemonRed.gbif it is not already. The sha1 sum should beea9bcae617fdf159b045185467ae58b2e4a48b9a, which you can verify by runningshasum PokemonRed.gb. - Move into the
baselines/directory:
cd baselines - Install dependencies:
pip install -r requirements.txt
It may be necessary in some cases to separately install the SDL libraries. - Run:
python run_pretrained_interactive.py
Interact with the emulator using the arrow keys and the a and s keys (A and B buttons).
You can pause the AI's input during the game by editing agent_enabled.txt
Note: the Pokemon.gb file MUST be in the main directory and your current directory MUST be the baselines/ directory in order for this to work.
This version still needs some tuning, but it can clear the first gym in a small fraction of the time and compute resources. It can work with as few as 16 cores and ~20G of RAM. This is the place for active development and updates!
- Previous steps 1-3
- Run:
python run_baseline_parallel_fast.py
The current state of each game is rendered to images in the session directory.
You can track the progress in tensorboard by moving into the session directory and running:
tensorboard --logdir .
You can then navigate to localhost:6006 in your browser to view metrics.
To enable wandb integration, change use_wandb_logging in the training script to True.
Map visualization code can be found in visualization/ directory.
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