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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Unified framework for robot learning with multi-physics/renderer support
- robot-learning
- robotics
- omniverse-kit-extension
- isaac-sim
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.
An Open Flexible Quadrotor Simulator
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
Gibson Environments: Real-World Perception for Embodied Agents
- computer-vision
- robotics
- simulator
- sim2real
An OpenAI gym wrapper for CARLA simulator
- carla-simulator
- autonomous-driving
- deep-reinforcement-learning
- imitation-learning
A simple and highly efficient RTS-game-inspired environment for reinforcement learning
HALO: Perceptive Humanoid Motion from Simulation
Maze Applied Reinforcement Learning Framework
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