My notes on reinforcement learning papers
-
Updated
Jun 14, 2018
My notes on reinforcement learning papers
Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"
A curated list of awesome Meta Reinforcement Learning
Learning to reinforcement learn for Neural Architecture Search
Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.
This repo contains the implementation of some new papers on some advanced topics of machine learning e.g. meta-learning, reinforcement-learning, meta-reinforcement-learning, continual-learning and etc.
Implementation of BIMRL: Brain Inspired Meta Reinforcement Learning - Roozbeh Razavi et al. (IROS 2022)
An implementation of Meta RL submitted as a course project for the course EE675A (Introduction to Reinforcement Learning)
A PyTorch Library for Meta-learning Research
Repo to reproduce the First-Explore paper results
Re-implementations of SOTA RL algorithms.
Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022
Code for FOCAL Paper Published at ICLR 2021
Official Implementation for "In-Context Reinforcement Learning from Noise Distillation"
Official Implementation for "In-Context Reinforcement Learning for Variable Action Spaces"
Toy meta-RL environments for testing algorithms implementations
π The code and methods offered in Awesome-META+: https://wangjingyao07.github.io/Awesome-Meta-Learning-Platform/
"λͺ¨λλ₯Ό μν λ©νλ¬λ" μ± μ λν μ½λ μ μ₯μ
GenReL-World is a general Reinforcement Learning framework to utilize various world models as environments for robot manipulation
Add a description, image, and links to the meta-rl topic page so that developers can more easily learn about it.
To associate your repository with the meta-rl topic, visit your repo's landing page and select "manage topics."