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
Farama Gymnasium API Wrapper for the DeepMind Control Suite and DeepMind Robot Manipulation Tasks
Implementation of k-Step Latent (KSL)
A novel approach to solve Contextual Reinforcement Learning
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