rl-feed

Implementation of a Q-learning based RL agent ( Fabber ) which learns to feed on snack in a grid world.

Trial

First clone the repository. Then, to train the RL agent

$ python main.py --learn

To save the model, add --output /path/to/output/directory to the command like,

$ python main.py --learn --output models

To test the RL agent, add --test to the command. To load a pretrained model, mention its path as --input /path/to/learned/model like,

$ python main.py --test --input models/model.pkl

Dependencies

• Numpy ( Used v1.8.2 )
• OpenCV ( Used 3.0.0 ); Just for visualisation, can be removed

Contribute

If you could think of any improvements to the project, please feel free to make a pull request.