Purpose of the project is to train pytorch model to play chrome dino game using own implementation of genetic algorithm.
├── game # game files | ├── static | ├── game.py | ├── player.py | ├── obstacles.py ├── models # trained models ├── genetic_algorithm.py # custom implementation of genetic algorithm ├── model.py # pytorch model used in project ├── train.py # training ├── play.py # playing vs trained model
TODO
As the task is not especially hard model used is quite simple. Input consists of 5 neurons, then fully connected 10-neurons hidden layer with relu activation. At the output there is one neuron (also fully connected), because task is just a binary classification (jump or dodge) it uses sigmoid activation.