Machine Learning Smart (mlSmart) game

• Library and packet requirements:

  • numpy
  • pygame
  • tensorflow
  • tflearn
  • scipy

• To start program: GameMLSmart.py

• About mlSmart game:

  • The project represents the Python implementation of the game for two players.

  • The player plays the game against Machine-Learning-Smart player (further a AI player).

  • The first part is to teach the MLS player some rules and possibilities of playing.

  • The second part is game simulation for one player and one AI player. AI for the first time see player, and compete with him.

  • AI player is implemented using neural network by TensorFlow library.

• Autors:

  • Stevan Milic (stevanmilic@gmail.com)
  • Ivan Nedic (nedicivan.nedic@gmail.com)

• The first step is to train the AI player and after that start game (see code in GameMLSmart.py)