Neural network simulation software.
Biased towards being more like a squishy brain and less like a traditional AI.
Running the program runs a "world". A world consists of a brain/model and an environment.
A brain consists of a network, a set of parameters, and choice of a model of a neuron to simulate.
An environment provides inputs to the brain and receives outputs.
Install python 3 and on a unix terminal or anaconda terminal on windows
git clone https://github.com/utilitarianexe/brains.git
cd brains/
pip install virtualenv
virtualenv venv
on unix source venv/bin/activate on windows C:\Users\'Username'\'path to repository'\venv\Scripts\activate
pip install -r requirements.txt
Optionally use rust acceleration if you have cargo installed
chmod a+x build_and_run.sh
./build_and_run.sh
Note this is a python 3 app with rust acceleration. You will need at least python 3. You can run the program without rust but it will be slower.
Runs in two display modes or with no display
python brains/main.py --epochs=5000 --world=easy --export_name=easy_network --display=""
Runs a simple brain for 2000000 steps(400 per epoch). Input from three neurons. One that fires randomly and a pair where at least one fires but which one is random. There are two output cells. If the same output cell fires as the input cell in the same row the network is rewarded and a win is recorded. The network starts out unbiased but will learn to fire the right output for the input.
Watch network run in real time by importing the brain you just trained.
python brains/main.py --environment=easy --import_name=easy_network --display=pygame
Or watch a more complex network and environment.
python brains/main.py --display pygame --world handwriting
Current input data for this mode is a small subset of https://www.kaggle.com/sachinpatel21/az-handwritten-alphabets-in-csv-format
Pressing space will cycle the modes (cells, weights, and none).
Clicking a cell will select it to
None will allow the program to run much faster.
I needed
MESA_LOADER_DRIVER_OVERRIDE=i965
to make pygame work on Ubuntu
Display potential graphs for each cell using pyplot
python brains/main.py --display pyplot --world stdp --epochs 5
You can export models to preserve changes to the network during a run using the export_name option. You can then import the model using the import_name option. You will also need the environment option, as this is not stored as part of the model. world is a combination of environment and model.
Using rust will massivly speed up the code.
cd iron_brains
cargo build --release
cp target/release/libiron_brains.so ../brains/iron_brains.so
The code is much more flexible than these options suggest.
Much more to come :-)
Run tests from root directory with
pytest