The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
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FinRL®: Financial Reinforcement Learning. 🔥
- deep-reinforcement-learning
- drl-trading-agents
- stock-trading
- drl-algorithms
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms
Machine learning, in numpy
- machine-learning
- neural-networks
- topic-modeling
- gaussian-mixture-models
PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
- reinforcement-learning
- reinforcement-learning-algorithms
- machine-learning
- gym
Infrastructure for continually self‑improving agents
Reproduction of SuperMimic (arXiv:2610.28480): learned differentiable world model + BPTT policy for G1 humanoid motion tracking, on mjlab/MuJoCo Warp
SuperMimic-UniLab: An Independent reproduction of SuperMimic on UniLab for whole-body humanoid motion tracking.
- amd
- motrixsim
- mujoco
- rocm
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".
- game-ai
- hearthstone
- reinforcement-learning
- rust
The official code of Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
The repository host gives no description.
Build RL environments for any domain from real cases that Browser Use agents mine from the web
Transformer-SRU LiDAR navigation for Unitree G1: Isaac Lab training, MuJoCo validation, and ROS 2 deployment.