GPU-accelerated NeuroEvolution of Augmenting Topologies (NEAT)
brax 开源项目推荐(37 个)
brax 话题在 GitHub 上没有填写简介,这里按 Star 数汇总最相关的热门仓库。
热门项目 前 20
按 Star 数排序展示前 20 个 · GitHub 共 37 个仓库The Simple Simulator: Simulation Made Simple
MetaDE is a GPU-accelerated evolutionary framework that optimizes Differential Evolution (DE) strategies via meta-level evolution. Supporting both JAX and PyTorch, it dynamically adapts mutation and crossover strategies for efficient large-scale black-box optimization.
Walkthroughs for DSL, AirSim, the Vector Institute, and more
a modular reinforcement learning library with JAX agents
An implementation of Short Horizon Actor Critic writen in Jax. Core algorithm written in the style of Brax, with several bits taken from Xu's original paper.
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA.
Brax Viewer is a real-time, interactive web viewer for monitoring reinforcement learning (RL) policies
纯JAX中的强化学习。
💡 Grasp - Pick-and-place with a robotic hand 👨🏻💻
Simple implementations of Cartesian Genetic Programming (CGP) and Linear Genetic Programming (LGP) in JAX
Relentlessly learning, persistently failing, but never surrendering.
[ICML 2024] Official environments and JAX-implementations for "Subequivariant Reinforcement Learning in 3D Multi-Entity Physical Environments"
Unitree Go2 terrain locomotion trained with MJX / MuJoCo Warp + Brax PPO on a single 8 GB GPU - 20.97M steps, 1536-768 MLP, stairs 0.03-0.05 m
[ICML 2026] Debate2Create: Robot Co-design via Multi-Agent LLM Debate
四足机器人 Go2 全栈控制:Convex MPC · RL(BC/PPO/域随机化)· 混合仲裁,同一套 72 试验推力协议下恢复率 94% —— 全程 CPU 训练,附与代码逐项一致的数学设计文档
APA-7 powered academic document editor online. Branded as "Acado".
A small humanoid robot you can talk to: walks with a reinforcement-learned policy, waves and dances, shows a face with lip sync and speaks - its brain is a local LLM you run yourself (Ollama or any OpenAI-compatible API). MuJoCo simulation, sim-to-real.
用于加速多智能体强化学习的程序化环境生成
Training a Unitree G1 Humanoid Robot to walk using PPO, JAX, and Brax. Achieved via End-to-End GPU Simulation (4096 parallel environments) and 200M timesteps of Curriculum Learning.
关于这个话题
- 清单取自 GitHub 话题页并按 Star 数排序,每次展示前 20 个项目;原始页面见 https://github.com/topics/brax。
- 该话题在 GitHub 上共有 37 个仓库, 本站收录的是其中最热门的 20 个,不是全量列表。
- Star / Fork 每日自动刷新一次,实时数据以 GitHub 为准。
- 当前 20 个项目累计 1118 Star,覆盖 5 种主要语言,数据更新于 2026-11-06。
- 中文介绍来自 GitHub 官方话题说明(github/explore)的机器翻译,可点「查看原文」对照;译文缺失时会先展示原文。