A maze-running mouse using the NuPIC cortial learning algorithm (CLA).
The code was written during the NuPIC Fall 2013 Hackathon in San Francisco, CA.
A demonstration of the project may be seen in the demo video.
The purpose of the project was to demonstrate how a hypothetical situation may be evaluated with a model. I characterized this as giving the CLA an imagination. A slow, prototype form of the idea is coded in learn/imagination.py. Look at mouse/mice.py (choose-best-move) for example usage. The gist is to provide a list of functions, each of which are applied to a copy of the original model to produce a prediction. The set of predictions (one per function) are returned.
Examine the main.py file to see the command-line arguments. Run either the 'dumb' or the 'smart' mouse with a few training and test iterations, as specified on the command-line.
Since the demo, the main change is that the initial location within the maze is randomized.
- Use a bigger, more interesting maze
- Provide a visualization of the maze and the mouse's movement (perhaps using curses module)
- Tweak the CLA model parameters