An elegant PyTorch deep reinforcement learning library.
Google DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.
Synapsa Commons: free, hands-on AI courses that run anywhere (Colab, Kaggle, Binder, Codespaces, Jupyter). EU AI Act conformity evidence, model validation, predictive maintenance, document extraction, retrieval and RAG, AI agents and MCP, a simulated humanoid. Every lesson autograded. From the team building Synapsa.
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Isaac Lab API, powered by MuJoCo-Warp, for RL and robotics research
A collection of robotics simulation environments for reinforcement learning
Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning
Python inverse kinematics based on MuJoCo.
MyoSuite is a collection of environments/tasks to be solved by musculoskeletal models simulated with the MuJoCo physics engine and wrapped in the OpenAI gym API.
Training a humanoid robot for locomotion using Reinforcement Learning
XuanCe: A Comprehensive and Unified Deep Reinforcement Learning Library
MuJoCo fruit fly body model and locomotion RL tasks
UniLab: A Heterogeneous Architecture for Robot RL Beyond GPU-Dominant Paradigms
Python library for Reinforcement Learning.
Unified Reinforcement Learning Framework
[CoRL '23] Dexterous piano playing with deep reinforcement learning.
A MuJoCo/Gym environment for robot control using Reinforcement Learning. The task of agents in this environment is pixel-wise prediction of grasp success chances.
A unified framework for robot learning
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