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Latest commit 116750f Jan 12, 2018

README.md

gamma-tic-tac-toe

introduction

Please see the following blog post for more information on this project https://blog.codecentric.de/en/2018/01/gamma-tictactoe-neural-network-machine-learning-simple-game/

compilation

Just clone the repository any run mvn clean compile package in the gamma-engine directory to compile the project.

running

In the gamm-engine directory just execute java -jar target/gamma-engine-0.0.1-SNAPSHOT.jar.

playing

configuration

The default configuration can be found from the application.properties in the resources-folder.

// Defines the amount of training runs executed before starting to play, default is 150. training.runs = 150

// Configuration related to selfplay selfplay.enabled = true selfplay.matches = 50 selfplay.games = 10000

Learning level

learning.stage = 1

Playing against human

humanplay.enabled = true