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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A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym)
A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities
- api
- gymnasium
- multi-agent-reinforcement-learning
- reinforcement-learning
A collection of environments for autonomous driving and tactical decision-making tasks
- reinforcement-learning
- autonomous-driving
- gymnasium-environment
PyBullet Gymnasium environments for single and multi-agent reinforcement learning of quadcopter control
- pybullet
- crazyflie
- robotics
- reinforcement-learning
Reinforcement Learning environments based on the 1993 game Doom :godmode:
- deep-learning
- reinforcement-learning
- python
- vizdoom
Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo.
An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
- reinforcement-learning
- parallel-processing
- cpp17
- pybind11
📈 Personae is a repo of implements and environment of Deep Reinforcement Learning & Supervised Learning for Quantitative Trading.
- reinforcement-learning
- supervised-learning
- stock-data
- trading
OpenAI Gym environments for an open-source quadruped robot (SpotMicro)
- openai-gym
- openai-gym-environments
- robotics
- tensorflow
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
- reinforcement-learning
- python
- deep-learning
- gym
Scalable, event-driven, deep-learning-friendly backtesting library
- reinforcement-learning
- deep-reinforcement-learning
- gym-environment
- openai-gym
An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments
Gibson Environments: Real-World Perception for Embodied Agents
- computer-vision
- robotics
- simulator
- sim2real
PettingZoo and Gymnasium bindings for popular reinforcement learning environments outside of Farama
- deepmind-control-suite
- deepmind-lab
- gymnasium
- reinforcement-learning
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
- gym
- pybullet
- reinforcement-learning
- control
This project provides a stock market environment using OpenGym with Deep Q-learning and Policy Gradient.
Environment for reinforcement-learning algorithmic trading models
Trading Environment(OpenAI Gym) + DDQN (Keras-RL)
A simple and highly efficient RTS-game-inspired environment for reinforcement learning
Trading Environment(OpenAI Gym) + PPO(TensorForce)
- ppo
- proximal-policy-optimization
- tensorforce
- trading
The official code of Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence
Trading environnement for RL agents, backtesting and training.
- trading
- backtesting
- reinforcement-learning-agent
- reinforcement-learning