CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
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Updated
Oct 28, 2020 - Python
CURL: Contrastive Unsupervised Representation Learning for Sample-Efficient Reinforcement Learning
RAD: Reinforcement Learning with Augmented Data
DrQ: Data regularized Q
This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
ExORL: Exploratory Data for Offline Reinforcement Learning
[DeepRL Workshop, NeurIPS-21] Recurrent Off-policy Baselines for Memory-based Continuous Control (RDPG, RTD3 and RSAC)
PyTorch implementation of "Sample-efficient Imitation Learning via Generative Adversarial Nets"
TensorFlow implementation of "Sample-efficient Imitation Learning via Generative Adversarial Nets"
Off-Policy Correction for Actor-Critic Algorithms in Deep Reinforcement Learning
Actor Prioritized Experience Replay
Contains PyTorch Implementation of the following off policy actor critic algorithms
This repository contains all of the Reinforcement Learning-related projects I've worked on. The projects are part of the graduate course at the University of Tehran.
PyTorch implementation of our work: "Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning"
solving a simple 4*4 Gridworld almost similar to openAI gym FrozenLake using Qlearning Temporal difference method Reinforcement Learning
DDPG and D4PG Continuous Control
This repository contains the implementation of a wide variety of Reinforcement Learning Projects in different applications of Bandit Algorithms, MDPs, Distributed RL and Deep RL. These projects include university projects and projects implemented due to interest in Reinforcement Learning.
Sample Policy Gradient
My content of CS294 Deep Reinforcement Learning course, conduced by Sergey Levine from UC Berkeley.
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