This small project applies Q-learning to the game of Tic-Tac-Toe using a deep neural network. As Tic-Tac-Toe is a very simple and also solved game, a simple rule-based or brute force approach could be used to easily implement an agent that plays flawlessly. Therefore the goal of this project is not to create an optimal bot for the game but to try out the concepts of reinforcement learning. The implementation is not by any means optimal.
-
Notifications
You must be signed in to change notification settings - Fork 1
This small project applies reinforcement learning to the game of Tic-Tac-Toe using a neural network.
License
0Zeta/Deep-TicTacToe
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Folders and files
Name | Name | Last commit message | Last commit date | |
---|---|---|---|---|
Repository files navigation
About
This small project applies reinforcement learning to the game of Tic-Tac-Toe using a neural network.
Topics
Resources
License
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published