There are then 3 main components: Vision, AI and Control which can be found in the robot directory. The vision finds lines and circles which are then sent to the board classes to compute valid states. The AI module uses a negamax algorithm with alpha beta pruning for efficiency. Control is designed specifically for our robot to compute the joint parameters and send these to our motor controller on the Lego EV3.

Boards is a package within robot that contains all the logic we need for each board game.

There is also helper.py containing useful classes such as Position and Player used by all modules.

1. Clone repo with $ git clone https://github.com/Mulac/ProjectCerebral.git
2. Install anaconda https://www.anaconda.com/distribution/ - we use conda enviroments to manage dependancies
3. cd into ProjectCerebral directory
4. conda env create -f environment.yml to create enviroment from yaml file
5. conda activate robot to enter the enviroment
6. python main.py to run the main loop