A curated list of fruit fly connectome projects: MaleCNS, FlyWire, brain simulations, embodied models, games, and research tools.
Reinforcement Learning GitHub Repositories (2026) · Open Source Tools
Discover the best Reinforcement Learning open source repositories on GitHub. Explore trending tools, live star counts, source code, and developer projects updated daily.
A native Mac App for LLM fine-tuning on Apple Silicon — fully on-device, fully open source.
Native C++ NES emulator with Python/Gymnasium APIs, vector execution, and cross-platform packaging.
Distributed Reinforcement Learning accelerated by Lightning Fabric
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformer
The RL Bridge for LLM-based Agent Applications. Made Simple & Flexible.
RLinf: Reinforcement Learning Infrastructure for Embodied and Agentic AI
Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research
Code for Watch Your Step: Anticipated Perception for Humanoid Locomotion, training a humanoid with a foothold prediction model.
[NeurIPS 2025 Spotlight] Reasoning Environments for Reinforcement Learning with Verifiable Rewards
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Multimodal RL training framework for diffusion & omni models
A fork of gym-retro with additional games, emulators and supported platforms
The complete post-training stack for LLMs, plus RL for any problem. SFT, DPO and multi-turn agentic RL, with evolutionary hyperparameter optimization built in.
Python library for Reinforcement Learning.
A unified framework for easy fine-tuning in Flow-Matching models
Keras based framework for neuro-symbolic LM systems
MuJoco Simulation on WebAssembly with Neural networks
EvoRL is a fully GPU-accelerated framework for Evolutionary Reinforcement Learning, implemented with JAX. It supports Reinforcement Learning (RL), Evolutionary Computation (EC), Evolution-guided Reinforcement Learning (ERL), AutoRL, and seamless integration with GPU-optimized simulation environments.