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
This is the pytorch implementation of Hindsight Experience Replay (HER) - Experiment on all fetch robotic environments.
RAD: Reinforcement Learning with Augmented Data
DrQ: Data regularized Q
SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning
Official PyTorch code for "Recurrent Off-policy Baselines for Memory-based Continuous Control" (DeepRL Workshop, NeurIPS 21)
ExORL: Exploratory Data for Offline Reinforcement Learning
⚡ Flashbax: Accelerated Replay Buffers in JAX
Causal RL: Reverse-Environment Network Integrated Actor-Critic Algorithm
Actor Prioritized Experience Replay
PyTorch implementation of "Sample-efficient Imitation Learning via Generative Adversarial Nets"
TensorFlow implementation of "Sample-efficient Imitation Learning via Generative Adversarial Nets"
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
Repository containing basic algorithm applied in python.
My content of CS294 Deep Reinforcement Learning course, conduced by Sergey Levine from UC Berkeley.
PyTorch implementation of "Sample-efficient Imitation Learning via Generative Adversarial Nets"
Contains PyTorch Implementation of the following off policy actor critic algorithms
Safe and Robust Experience Sharing for Deterministic Policy Gradient Algorithms
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