Genetic-Birds-Simulator

A simulation of birds using neural networks and a genetic algorithm.

About

The goal is to teach birds (triangles) how to catch food (circles) by using learning mechanisms that simulate natural evolution.

Motivation

This project is a kind of sequel to MLP-Digits-Recognition, an implementation of a neural network from scratch. This time, I used this great tutorial as a starting point, to train the neural network with a genetic algorithm, instead of backpropagation.

Technical description

• The lib-neural-network library contains an implementation of a simple, non-optimized FFNN (Feed-Forward Neural Network).
• The lib-genetic-algorithm library implements a genetic algorithm, which selects, crossovers, and mutates individuals.
• The lib-simulation back-end library holds the world, birds and food.
• The lib-simulation-wasm middle-end library is a WebAssembly wrapper for lib-simulation.
• The npm app contains the front-end elements for the simulation and is responsible of displaying birds, food, and to handle user input.

The Genetic Algorithm is build to work with multiple selection, crossover, and mutation algorithms. The ones currently implemented are Roulette Wheel Selection, Uniform Crossover, and Gaussian Mutation.

Running the simulation

The simulation can run in any browser. To try it yourself, you will need:

• rustc and cargo installed, for the back-end code.
• wasm-pack, to compile Rust code into WebAssembly
• npm for the front-end simulation

Note: some packages used seem to conflict with latest npm versions. If you encounter any issues, try to change npm version using npm install npm@9.5.0 -g, and to add the following node option: export NODE_OPTIONS=--openssl-legacy-provider.

In the Genetic-Birds-Simulator root folder, you can make sure that everything is working by running:

$ cargo check && cargo test

Then, compile the Rust code to WebAssembly by running:

$ cd libs/simulation-wasm
$ wasm-pack build --release

Finally, launch the front-end simulation by running:

$ cd ../..
$ cd www
$ npm run start

If everything goes as planned, your terminal will display:

...
｢wds｣: Project is running at http://localhost:8080/
...
｢wdm｣: Compiled successfully.

Enter http://localhost:8080/ (or any other given address) in your favorite web browser, and the simulation should start.

Parameters

You can play with the parameters of the simulation. They are defined as constants in lib-simulation. The lib.rs file contains general parameters, and the eye.rs file contains constants that define the FOV (Field of View) of the birds.

lib.rs includes:

• Minimum and maximum speed of the birds.
• Maximum change of speed and rotation that the brain can ask for, in one step.
• The GENERATION_LENGTH, number of steps between two evolutions.
• Gaussian mutation parameters: the chance of mutation, and coefficient of change.
• The number of birds and foods in the simulation.

eye.rs includes:

• FOV_RANGE, the maximum distance that the eye can see.
• FOV_ANGLE, the angle that the eye covers.
• CELLS, the number of subdivisions of the FOV. The number of cells is also the number of neurons in the input layer of the brain's neural network.

One last parameter is available in the index.js file of the front-end simulation, and is called STEPS_PER_FRAME. By default, your web browser will try to run the program at roughly 60 frames per second; hence, if STEPS_PER_FRAME = 1, only 60 steps will be simulated per seconds. To speed up this process, use, for example, STEPS_PER_FRAME = 10, which will try to compute 600 steps per second.

License

This work is licensed under the CC-BY-NC-SA 4.0 license.