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"

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.

Code for FOCAL Paper Published at ICLR 2021

Repo to reproduce the First-Explore paper results

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

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

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

Xenoverse is a collection of randomized RL, Language, and general-purpose simulation environments, designed for training General-Purpose Learning Agents (GLAs).

🌈 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