What is Tron?

Tron is a simple 2-player snake-style game where players try to avoid walls and any already-visited locations. JimmyNewTron is a version which has been rewritten and supports training a neural network model to serve as a non-player character. The included model has been trained for about 1000 frames.

Screenshot:

Quick Start: At the top of the code, choose a mode for player 1 (blue) and 2 (yellow).

- keyboard        - use WASD for p1 and arrows for p2
- random          - player moves randomly
- ai_load_trained - load model from disk, use it to make movement decisions
- ai_retrain      - load model from disk, use it to make movement decisions, train model based on game data
- ai_train_random - create a new model, move player randomly, train model based on game data
                    note: this will overwrite your existing model

Additional Options: These can be changed if desired

- filename              - choose target for TFlearn data on disk (default: "TronNN.tflearn")
- obstacles             - choose the number of random hazards in the game (0+)   
- training_games        - if one of the players selected ai_retrain or ai_train_random, this limits the number of automatic
                          training games which are played. Select 0 if you do not want it to automatically play games.
- games_before_training - specify the number of games to play before training and flushing the data
- speed                 - choose the refresh rate. 10 is slow, 15 is normal, 60 is recommended for training

There also exists an option to modify the radius of cells which the AI model can 'see', but this option requires retraining the network with ai_train_random after being changed. Be careful!

When the round is completed, press the space bar to replay. ESC quits the game.

NOTE: This game requires pygame and tensorflow/TFLearn to run.