An elegant PyTorch deep reinforcement learning library.
-
Updated
Sep 10, 2024 - Python
An elegant PyTorch deep reinforcement learning library.
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Imitation learning algorithms with Co-training for Mobile ALOHA: ACT, Diffusion Policy, VINN
Reinforcement Learning Coach by Intel AI Lab enables easy experimentation with state of the art Reinforcement Learning algorithms
Clean PyTorch implementations of imitation and reward learning algorithms
[PAMI'23] TransFuser: Imitation with Transformer-Based Sensor Fusion for Autonomous Driving; [CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
BabyAI platform. A testbed for training agents to understand and execute language commands.
Implementation of Inverse Reinforcement Learning (IRL) algorithms in Python/Tensorflow. Deep MaxEnt, MaxEnt, LPIRL
Decision Intelligence Platform for Autonomous Driving simulation.
Train robotic agents to learn pick and place with deep learning for vision-based manipulation in PyBullet. Transporter Nets, CoRL 2020.
An OpenAI gym wrapper for CARLA simulator
[CoRL 2024] HumanPlus: Humanoid Shadowing and Imitation from Humans
A unified framework for robot learning
IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks
TensorFlow2 Reinforcement Learning
🤖 The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation
Imitation learning algorithms
(CVPR 2022) A minimalist, mapless, end-to-end self-driving stack for joint perception, prediction, planning and control.
[ICCV'21] NEAT: Neural Attention Fields for End-to-End Autonomous Driving
(JAIR'2022) A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II. JAIR = Journal of Artificial Intelligence Research.
Add a description, image, and links to the imitation-learning topic page so that developers can more easily learn about it.
To associate your repository with the imitation-learning topic, visit your repo's landing page and select "manage topics."