PyTorch implementation of Soft Actor-Critic (SAC)
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Updated
Dec 5, 2021 - Jupyter Notebook
PyTorch implementation of Soft Actor-Critic (SAC)
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
RAD: Reinforcement Learning with Augmented Data
OpenAI Gym wrapper for the DeepMind Control Suite
DrQ: Data regularized Q
PyTorch implementation of Soft Actor-Critic + Autoencoder(SAC+AE)
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
A Multi-Task Dataset for Simulated Humanoid Control
Proto-RL: Reinforcement Learning with Prototypical Representations
Convert DeepMind Control Suite to OpenAI gym environments.
Base Mujoco Gymnasium environment for easily controlling any robot arm with operational space control. Built with dm-control PyMJCF for easy configuration.
PyTorch Implementation of Visual GAIL in Atari Games
Wrapper around dm_control to provide a gym like interface and vice-versa
This repository is a collection of widely used self-supervised auxiliary losses used for learning representations in reinforcement learning.
Gymnasium integration for the DeepMind Control (DMC) suite
Control Ordinary Differential Equations with deep reinforcement learning
Implementation of k-Step Latent (KSL)
Farama Gymnasium API Wrapper for the DeepMind Control Suite and DeepMind Robot Manipulation Tasks
A Deep Reinforcement Learning (DeepRL) package for RL algorithm developers.
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