Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
A toolkit for reproducible reinforcement learning research.
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
Scalable, event-driven, deep-learning-friendly backtesting library
PettingZoo and Gymnasium bindings for popular reinforcement learning environments outside of Farama
A light-weight deep reinforcement learning framework for portfolio management. This project explores the possibility of applying deep reinforcement learning algorithms to stock trading in a highly modular and scalable framework.
This trading-gym is the first trading for agent to train with episode of short term trading itself.
Trading environnement for RL agents, backtesting and training.
Transformer-SRU LiDAR navigation for Unitree G1: Isaac Lab training, MuJoCo validation, and ROS 2 deployment.