A PyTorch Library for Meta-learning Research

Collections of robotics environments geared towards benchmarking multi-task and meta reinforcement learning

TorchOpt is an efficient library for differentiable optimization built upon PyTorch.

Simple (but often Strong) Baselines for POMDPs in PyTorch, ICML 2022

Re-implementations of SOTA RL algorithms.

"모두를 위한 메타러닝" 책에 대한 코드 저장소

Official Implementation for "In-Context Reinforcement Learning for Variable Action Spaces"

Code for FOCAL Paper Published at ICLR 2021

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.

Repo to reproduce the First-Explore paper results

Implementation of our paper "Meta Reinforcement Learning with Task Embedding and Shared Policy"

Reimplementing existing learning-based ABR algorithms for dynamic video streaming. These algorithms were implemented with Pytorch and python3

A curated list of awesome Meta Reinforcement Learning

Official Implementation for "In-Context Reinforcement Learning from Noise Distillation"

Implementation of Model-Agnostic Meta-Learning (MAML) applied on Reinforcement Learning problems in TensorFlow 2.

My notes on reinforcement learning papers

🌈 The code and methods offered in Awesome-META+: https://wangjingyao07.github.io/Awesome-Meta-Learning-Platform/

Implementation of BIMRL: Brain Inspired Meta Reinforcement Learning - Roozbeh Razavi et al. (IROS 2022)

Toy meta-RL environments for testing algorithms implementations

Learning to reinforcement learn for Neural Architecture Search