Ranked by Attention Score: stars gained over the last 7 complete days
30 repositories by Attention Score · Oct 30, 2026 – Nov 5, 2026 (UTC)
Official code for "Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models" (ICRA 2026): Flow Policy Optimization for pi0
FinRL®: Financial Reinforcement Learning. 🔥
Whole-body motion tracking for the Unitree G1 in about 3 minutes on one GPU: return 0.82 with 0/40 clips failed at the first checkpoint for all seeds, >=10.9x faster than SuperMimic + EMA; 3.2 min with fine checkpoints, 2.74 min without LR annealing (world model + Muon + overlapped CUDA streams, mjlab)
Reproduction of SuperMimic (arXiv:2610.28480): learned differentiable world model + BPTT policy for G1 humanoid motion tracking, on mjlab/MuJoCo Warp
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".
A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
An elegant PyTorch deep reinforcement learning library.
Playing Pokemon Red with Reinforcement Learning
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
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
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
An offline deep reinforcement learning library
The official code of Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
A collection of environments for autonomous driving and tactical decision-making tasks
Tensorflow implementation of Human-Level Control through Deep Reinforcement Learning
Clean PyTorch implementations of imitation and reward learning algorithms
📈 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
Gibson Environments: Real-World Perception for Embodied Agents
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
[ICRA] Crowd-aware Robot Navigation
Environment for reinforcement-learning algorithmic trading models
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Python application to setup and run streaming (contextual) bandit experiments.