1 unstable release
0.1.0 | Oct 1, 2020 |
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#1750 in Algorithms
40KB
1K
SLoC
rsneat
rsneat is an open source crate that implements the NEAT genetic algorithm. The implementation is based off of the original 2002 paper.
The purpose of this project was to help me learn Rust and the Rust ecosystem. This project should probably not be used for a serious project without extreme caution.
Example
This example uses the neat simulation to find an algorithm that computes the xor function
let mut neat = Neat::new();
let mut founder = Genome::new(3, 1);
founder.add_connection(0, 3, 0.0, &mut neat);
founder.add_connection(1, 3, 0.0, &mut neat);
founder.add_connection(2, 3, 0.0, &mut neat);
let mut pop = Population::clone_from(founder, &neat);
loop {
let mut correct = true;
for (mut n, fitness) in pop.iter_fitness() {
correct = true;
let data = [
(vec![0.0, 0.0, 1.0], 0.0, false),
(vec![0.0, 1.0, 1.0], 1.0, true),
(vec![1.0, 0.0, 1.0], 1.0, true),
(vec![1.0, 1.0, 1.0], 0.0, false),
];
let mut error = 0.0;
*fitness = 0.0;
for (input, output, c) in data.iter() {
for _ in 0..5 {
let _ = n.activate(input.clone().into_iter());
}
let result = n.activate(input.clone().into_iter()).next().unwrap();
let result_error = (result - output).abs();
error += result_error;
let result = result >= 0.5;
if *c != result {
correct = false;
}
n.reset();
}
*fitness += 4.0 - error;
*fitness *= *fitness;
if correct {
break;
}
}
if correct {
pop.champ().write(&mut std::fs::File::create("champ.neat").unwrap()).unwrap();
println!("Got a champ after {} gens!", pop.gen());
}
pop.evaluate_generation(&mut neat);
}
Dependencies
~2MB
~36K SLoC