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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Machine learning, in numpy
- machine-learning
- neural-networks
- topic-modeling
- gaussian-mixture-models
A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
An elegant PyTorch deep reinforcement learning library.
- pytorch
- policy-gradient
- dqn
- double-dqn
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
- wandb
- reinforcement-learning
- pytorch
- python
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.
- c-plus-plus
- machine-learning
- online-learning
- contextual-bandits
Infrastructure for continually self‑improving agents
Deep Learning and Reinforcement Learning Library for Scientists and Engineers
- tensorlayer
- deep-learning
- tensorflow
- neural-network
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
- api
- gymnasium
- multi-agent-reinforcement-learning
- reinforcement-learning
Tensorforce: a TensorFlow library for applied reinforcement learning
- reinforcement-learning
- tensorflow
- deep-reinforcement-learning
- tensorflow-library
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
- pybullet
- crazyflie
- robotics
- reinforcement-learning
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
PGPortfolio: Policy Gradient Portfolio, the source code of "A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem"(https://arxiv.org/pdf/1706.10059.pdf).
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
- reinforcement-learning
- supervised-learning
- stock-data
- trading
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
Gibson Environments: Real-World Perception for Embodied Agents
- computer-vision
- robotics
- simulator
- sim2real
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
Reinforcement learning library(framework) designed for PyTorch, implements DQN, DDPG, A2C, PPO, SAC, MADDPG, A3C, APEX, IMPALA ...
- reinforcement-learning
- deep-learning
- pytorch
- pytorch-reinforcement-learning
A simple and highly efficient RTS-game-inspired environment for reinforcement learning
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.
Maze Applied Reinforcement Learning Framework
Official code for "Reinforcement Fine-Tuning of Flow-Matching Policies for Vision-Language-Action Models" (ICRA 2026): Flow Policy Optimization for pi0
- aloha
- flow-matching
- icra2026
- jax
Workbench for practical machine learning in Ruby.
- machine-learning
- machine-learning-algorithms
- neural-network
- neural-networks