A students Project on GO.
The game Go is perhaps one of the most challenging of classical games for artificial intelligence due to its huge search space and the difficulty of evaluating moves and board positions. The goal of this project is to develop from scratch a learning machine, e.g., based on a neural network architecture, that plays at best Go on a reduced size board. The network would be trained with the results of gaming against minimax algorithms of different moves tree depths. For detailed info contact M.Sc. Bernhard Werner at M10 Technische Universität München.
On using GitHub:
- create an account on GitHub
- become a contributor on this project
- install Git (best use default options when asked)
- optionally: Install a GUI of your choice for Git (I use "GutHub Desktop")
- clone the project to your Desktop Computer. You can use the GUI for that.
- pull and Merge as you like!