Snail jumper

Neuroevolution game assignment.
Fall 2021 - Computer Intelligence.

This game has been developed as an assignment for students at Amirkabir University of Technology to apply neuroevolution using a simple game.

You can find project's description in Persian in this file.

How to run

Requirements

• Python 3.8 or higher
• Pygame 2.0.1 or higher

Run

• Clone the repository
• Run python game.py

How to play

This game has two modes: Manual and Neuroevolution.

Manual

In this mode, you can control the snail using the space bar.

Neuroevolution

In this mode, the snail is controlled by a neural network.

Development

• Create a simple game use pygame
• Create a simple neural network
• Create a simple genetic algorithm
• Create a simple neuroevolution algorithm
• Create a simple neuroevolution algorithm with genetic algorithm

Project structure

• game.py: Main file to run the game
  • include all other files
• nn.py: Neural network class
  • NeuralNetwork class
    • __init__: initialize neural network
    • forward: feed forward function
    • batch_normalize: normalize input
    • activation: activation function
      • sigmoid: use sigmoid activation function
• evolution.py: Evolution class
  • Evolution class
    • __init__: initialize evolution
    • next_population_selection: select next population from current population and wrire to average.txt use Q-Tournament if you want to use SUS selection, uncomment line 46 to 62 and comment line 65 to 74
    • generate_new_population: generate new population from current population
    • mutate: mutate a population
    • clone_player: clone a player
• player.py: Player class
  • Player class
    • __init__: initialize player
    • flip_player_horizontally: flip player horizontally
    • update: update player use neural network or keyboard
    • animation_state: animate player
    • apply_gravity: apply gravity to player
    • player_input: get player input in manual mode
    • change_gravity: change gravity
    • think: get output from neural network and change gravity
    • make_inputs: make inputs for neural network
    • batch_normalize: normalize inputs
• plot.py: Plot class
  • plot average score and best score from average.txt
• average.txt: save average score and min score from each generation
  • x y z : max score, min score, average score you can use this file to plot average score and best score

plots of two different runs are:

• first-run
• second-run

Contributors

SoroushMehraban
mohamadch91

Orginal Repository

SoroushMehraban/SnailJumper