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acwj

A Compiler Writing Journey

baselines

OpenAI Baselines: high-quality implementations of reinforcement learning algorithms

clash

Clash for Windows & Mac 自用稳定分流规则、参考配置

darp

deep-reinforcement-learning-algorithms-with-pytorch

Clean, Robust, and Unified PyTorch implementation of popular DRL Algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

drl-dm_control

Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

drl-mujoco-cassie-mujoco-sim

A simulation library for Agility Robotics' Cassie robot using MuJoCo

end-to-end-drl-for-fjsp

This is the official code of the publised paper 'A Multi-action Deep Reinforcement Learning Framework for Flexible Job-shop Scheduling Problem'

esp-idf

Espressif IoT Development Framework. Official development framework for Espressif SoCs.

freenove_ws2812_lib_for_esp32

full_coverage_path_planner

Full coverage path planning provides a move_base_flex plugin that can plan a path that will fully cover a given area

grok-1

Grok open release

gymnasium

An API standard for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)

hello-algo

《Hello 算法》：动画图解、一键运行的数据结构与算法教程，支持 Python, C++, Java, C#, Go, Swift, JS, TS, Dart, Rust, C, Zig 等语言。English edition ongoing

kuka-reach-drl

Train kuka robot reach a point with deep rl.

learnmujoco

新版Mujoco学习记录

machinelearning

My blogs and code for machine learning. http://cnblogs.com/pinard

mlimpl

This repository collects some codes that encapsulates commonly used algorithms in the field of machine learning. Most of them are based on Numpy, Pandas or Torch. You can deepen your understanding to related model and algorithm or revise it to get the customized code belongs yourself by referring to this repository.

mujoco

Multi-Joint dynamics with Contact. A general purpose physics simulator.

mytinystl

Achieve a tiny STL in C++11

pbrs-humanoid

rb_tree

红黑树的实现

rcpp

Optimal coverage path planning

reward-learning-rl

[RSS 2019] End-to-End Robotic Reinforcement Learning without Reward Engineering

rk3588-yolo-demo

The project is a multi-threaded inference demo of Yolo running on the RK3588 platform, which has been adapted for reading video files and camera feeds. The demo uses the Yolov8n model for file inference, with a maximum inference frame rate of up to 100 frames per second.

rknn-cpp-multithreading

A simple demo of yolov5s running on rk3588/3588s using c++ (about 142 frames). / 一个使用c++在rk3588/3588s上运行的yolov5s简单demo(142帧/s)。

rknn-multi-threaded

A simple demo of yolov5s running on rk3588/3588s using Python (about 72 frames). / 一个使用Python在rk3588/3588s上运行的yolov5s简单demo(大约72帧/s)。

rknn-toolkit2

rl-mpc-locomotion

Deep RL for MPC control of Quadruped Robot Locomotion