C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
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A curated list of awesome links and software libraries that are useful for robots.
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
Computational framework for reinforcement learning in traffic control
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
Modular Reinforcement Learning (RL) library (implemented in PyTorch, JAX, and NVIDIA Warp) with support for Gymnasium/Gym, NVIDIA Isaac Lab, MuJoCo Playground and other environments
Scalable, event-driven, deep-learning-friendly backtesting library
Gibson Environments: Real-World Perception for Embodied Agents
PettingZoo and Gymnasium bindings for popular reinforcement learning environments outside of Farama
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
Deepdrive is a simulator that allows anyone with a PC to push the state-of-the-art in self-driving
👉 CARLA resources such as tutorial, blog, code and etc https://github.com/carla-simulator/carla
[ICRA] Crowd-aware Robot Navigation
A curated list of Monte Carlo tree search papers with implementations.
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
🦆 Microduck 飞特 HD1910 机器人鸭复刻：单脚独立实机、现成动作模型、中文中控、自制 HAT/IMU 与三步教程。正常复刻无需训练。Feetech HD1910 Microduck replica: one-legged balance, ready-to-use models, Chinese console, custom HAT/IMU & 3-step build guides. No training required.
Scikit-learn for Recursive Self-improvement (RSI). A modular framework for recursive harness evolution.
Open, source-backed catalog of computer-use agents: reviewed papers, GUI models, datasets, benchmarks, tools, and reusable JSONL/SQLite data.
Deep Reinforcement Learning for de-novo Drug Design
Maze Applied Reinforcement Learning Framework
TavernGym and TavernBench: a faithful, full-content Hearthstone Battlegrounds simulator with an RL interface, and a 960-task decision benchmark. Code and data for "Build, Don't Play".
Free Course : Data, Machine Learning, Deep Learning and AI Engineering, the long way round: the math, the code, the systems and the security. 173 lessons, 166 runnable labs, no shortcuts. Free under CC BY-NC 4.0.
Trading environnement for RL agents, backtesting and training.
Building a population of models that trade crypto and mutate iteratively