Hikaru

MujocoTutorials. These tutorials cover a variety of common robotics tasks and controllers, providing a comprehensive introduction to using Mujoco for robotics simulation. Each tutorial is designed to be self-contained within a single file for ease of use and understanding.

MuJoCo-Tutorial. Tutorial on how to get started with MuJoCo Simulation Platform. MuJoCo stands for Multi-Joint dynamics with Contact. It was acquired and made freely available by DeepMind in October 2021, and open sourced in May 2022. Feel free to contribute. Show your support by ✨this repository.

mujoco_mpc. Real-time behaviour synthesis with MuJoCo, using Predictive Control

newton. An open-source, GPU-accelerated physics simulation engine built upon NVIDIA Warp, specifically targeting roboticists and simulation researchers.

mujoco_ros2_control. C++

Manipulator-Mujoco. Base Mujoco Gymnasium environment for easily controlling any robot arm with operational space control. Built with dm-control PyMJCF for easy configuration.

cs249r_book. Machine Learning Systems

imgui. Dear ImGui: Bloat-free Graphical User interface for C++ with minimal dependencies

BehaviorTree.CPP. Behavior Trees Library in C++. Batteries included.

DearPyGui. Dear PyGui: A fast and powerful Graphical User Interface Toolkit for Python with minimal dependencies

rclpy. rclpy (ROS Client Library for Python)

mikanos-build. Build and run scripts for MikanOS

mikanos. Educational Operating System

book_ros2. C++

rm_robot. ROS was developed for the Realman robot (http://www.realman-robotics.com/).

cartesian_controllers. A set of Cartesian controllers for the ROS1 and ROS2-control framework.

ultralytics. Ultralytics YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking

rl. A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

pytorch. Tensors and Dynamic neural networks in Python with strong GPU acceleration

baklavajs. Graph / node editor in the browser using VueJS

misc2. C

modern-js-cheatsheet. Cheatsheet for the JavaScript knowledge you will frequently encounter in modern projects.

leohuynh.dev. My personal space on the cloud where I document my programming journey, sharing lessons, insights, and resources for fellow developers.

tailwind-nextjs-starter-blog. This is a Next.js, Tailwind CSS blogging starter template. Comes out of the box configured with the latest technologies to make technical writing a breeze. Easily configurable and customizable. Perfect as a replacement to existing Jekyll and Hugo individual blogs.

computer-8bits. A basic 8-bits computer created with LogiSim digital circuit simulator :computer:

loguru. Python logging made (stupidly) simple

Implicit-Q-Learning. PyTorch implementation of the implicit Q-learning algorithm (IQL)

cleanrl. High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)

CORL. High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC

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

CQL. PyTorch implementation of the Offline Reinforcement Learning algorithm CQL. Includes the versions DQN-CQL and SAC-CQL for discrete and continuous action spaces.

awesome-math. A curated list of awesome mathematics resources

d4rl-pybullet. Datasets for data-driven deep reinforcement learning with PyBullet environments

RNN-RL. Experiments with reinforcement learning and recurrent neural networks

implicit_q_learning. Python

Implicit-Language-Q-Learning. Official code from the paper "Offline RL for Natural Language Generation with Implicit Language Q Learning"

trajectory-transformer. Code for the paper "Offline Reinforcement Learning as One Big Sequence Modeling Problem"

learnopencv. Learn OpenCV : C++ and Python Examples

ildoonet-tf-pose-estimation. Python

DTQN. Deep Transformer Q-Networks for Partially Observable Reinforcement Learning

Transformer-based-Deep-Reinforcement-Learning-for-Video-Games. Jupyter Notebook

TD3. Author's PyTorch implementation of TD3 for OpenAI gym tasks

IQL-PyTorch. A PyTorch implementation of Implicit Q-Learning

TD3_BC. Author's PyTorch implementation of TD3+BC, a simple variant of TD3 for offline RL

OfflineRL. A collection of offline reinforcement learning algorithms.

awesome-mac.  This project is dedicated to collecting high-quality macOS software and organizing them systematically by different categories for easy search and use.

awesome-rl. Reinforcement learning resources curated

awesome-offline-rl. An index of algorithms for offline reinforcement learning (offline-rl)

d3rlpy. An offline deep reinforcement learning library

transformers. 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

decision-transformer. Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.

google-research. Google Research

awesome-decision-transformer. A curated list of Decision Transformer resources (continually updated)

DI-engine. OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

g-mlp. PyTorch implementation of Pay Attention to MLPs

g-mlp-pytorch. Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch

RL-book. Python

xournalpp. Xournal++ is a handwriting notetaking software with PDF annotation support. Written in C++ with GTK3, supporting Linux (e.g. Ubuntu, Debian, Arch, SUSE), macOS and Windows 10. Supports pen input from devices such as Wacom Tablets.

PettingZoo. A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities

spinningup. An educational resource to help anyone learn deep reinforcement learning.

baby-steps-of-rl-ja. Pythonで学ぶ強化学習 -入門から実践まで- サンプルコード

stable-baselines3. PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.

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

RL-Adventure. Pytorch Implementation of DQN / DDQN / Prioritized replay/ noisy networks/ distributional values/ Rainbow/ hierarchical RL

Rainbow. Rainbow: Combining Improvements in Deep Reinforcement Learning

tianshou. An elegant PyTorch deep reinforcement learning library.

pytorch_advanced. 書籍「つくりながら学ぶ! PyTorchによる発展ディープラーニング」の実装コードを配置したリポジトリです