Working-in-progress
Implementation of NeuroEvolution of Augmenting Topologies NEAT http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf
This implementations uses a CTRNN based onOn the Dynamics of Small Continuous-Time Recurrent Neural Network (Beer, 1995) http://www.cs.uvm.edu/~jbongard/2014_CS206/Beer_CTRNNs.pdf
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
source $HOME/.cargo/env
To speed up tests, run them with --release (XOR classification/simple_sample should take less than a minute)
cargo test --release
cargo run --release --example simple_sample --features=telemetry
then go to http://localhost:3000 to see how neural network evolves
Install python dependencies
sudo apt install python3
sudo apt install python3-pip
sudo apt install libpython3.8-dev
sudo apt-get remove swig
sudo apt-get install swig3.0
sudo ln -s /usr/bin/swig3.0 /usr/bin/swig
sudo pip3 install gym
sudo pip3 install gym[box2d]
sudo apt install python3-openglRun test
cargo run --release --example openai --features=openai,telemetry
Update to the latest version of Windows (>version 1607, "Anniversary Update")
Enable Windows Subsystem for Linux (WSL)
Open cmd, run bash
Install python & gym (using sudo, and NOT PIP to install gym). So by now you should probably be able to run things and get really nasty graphics related errors. This is because WSL doesn't support any displays, so we need to fake it.
Install vcXsrv, and run it (you should just have a little tray icon)
In bash run "export DISPLAY=:0" Now when you run it you should get a display to pop-up, there may be issues related to graphics drivers. Sadly, this is where the instructions diverge if you don't have an NVIDIA graphics card.
Get the drivers: "sudo apt-get install nvidia-319 nvidia-settings-319 nvidia-prime"
Run!
Create a new cargo project:
Add rustneat to Cargo.toml
[dependencies]
rustneat = "0.2.1"
Then use the library i.e. to implement the above example, use the library as follows:
extern crate rustneat;
use rustneat::Environment;
use rustneat::Organism;
use rustneat::Population;
struct XORClassification;
impl Environment for XORClassification {
fn test(&self, organism: &mut Organism) -> f64 {
let mut output = vec![0f64];
let mut distance: f64;
organism.activate(&vec![0f64, 0f64], &mut output);
distance = (0f64 - output[0]).abs();
organism.activate(&vec![0f64, 1f64], &mut output);
distance += (1f64 - output[0]).abs();
organism.activate(&vec![1f64, 0f64], &mut output);
distance += (1f64 - output[0]).abs();
organism.activate(&vec![1f64, 1f64], &mut output);
distance += (0f64 - output[0]).abs();
(4f64 - distance).powi(2)
}
}
fn main() {
let mut population = Population::create_population(150);
let mut environment = XORClassification;
let mut champion: Option<Organism> = None;
while champion.is_none() {
population.evolve();
population.evaluate_in(&mut environment);
for organism in &population.get_organisms() {
if organism.fitness > 15.9f64 {
champion = Some(organism.clone());
}
}
}
println!("{:?}", champion.unwrap().genome);
}Check style guidelines with:
rustup component add rustfmt-preview
cargo fmt
Thanks for the icon nerves by Delwar Hossain from the Noun Project
NeuroEvolution of Augmenting Topologies NEAT http://nn.cs.utexas.edu/downloads/papers/stanley.ec02.pdf
On the Dynamics of Small Continuous-Time Recurrent Neural Network (Beer, 1995) http://www.cs.uvm.edu/~jbongard/2014_CS206/Beer_CTRNNs.pdf
An Investigation into the Dynamics of a Continuous Time Recurrent Neural Network Node http://www.tinyblueplanet.com/easy/FCSReport.pdf
http://indy9000.github.io/posts/analysis-of-a-simple-ctrnn.html http://indy9000.github.io/posts/analysis-of-a-simple-ctrnn.html
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