A collection of Deep Neuroevolution resources or evolutionary algorithms applying in Deep Learning (constantly updating)

Automated Design of Agentic Systems

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

Differentiable neuron simulations with biophysical detail on CPU, GPU, or TPU.

RL Environments in JAX 🌍

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

A monitor of resources

Keep track of your results

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.

An implementation of CoDeepNEAT using pytorch with extensions

Overview of the current state of 'Neuroevolution of Augmenting Topologies' as a seminar paper

The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.

Deep Evolvable-Substrate HyperNEAT - Extending ES-HyperNEAT with Multiple Substrates in an Evolving Topology

A playbook for systematically maximizing the performance of deep learning models.

Evolving Artificial Neural Networks (a.k.a. Neuroevolution) in parallel using MPI for Python.

Evolution Strategies in JAX 🦎

PROFINET device stack for embedded devices

Dopamine is a research framework for fast prototyping of reinforcement learning algorithms.

A collection of wrappers for Gymnasium and PettingZoo environments (being merged into gymnasium.wrappers and pettingzoo.wrappers

⏩ Continue is the leading open-source AI code assistant. You can connect any models and any context to build custom autocomplete and chat experiences inside VS Code and JetBrains

Aerial Gym Simulator - Isaac Gym Simulator for Aerial Robots

Accelerated Quality-Diversity

Autonomous software engineer right in your IDE, capable of reading/writing files, executing commands, and more with your permission every step of the way.

Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way.

Deep-Reinforcement-Learning-Hands-On-Second-Edition, published by Packt

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.