Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.

[NeurIPS2021] Learning Distilled Collaboration Graph for Multi-Agent Perception

master thesis

微电网优化调度模型

Iching is a deep meta reinforcement learning quantitative trading platform.

Decoupled Reward-free ExplorAtion and Execution for Meta-reinforcement learning

Customized environment utilizing the OpenAI Gym library for controlling battery energy storage systems in multi-microgrids

a novel algo for meta-MARL; 元-多智能体强化学习算法

Code snippets of Meta Reinforcement Learning algorithms

Proximal Policy Optimization with Model-Agnostic Meta-Learning for Battery Energy Storage System Management in a Multi-Microgrid

Reimplementation of MAML and Reproduction of the Results in the simple Reinforcement Learning setup

Code examples of the neural net architecture for RL algorithm with possibility using of several operations at one moment

Implementation of 'Model Agnostic Meta Learning' in pytorch

meta reinforcement learning project for transportation

Multi Agent IPPO implementation for Meta RL

Meta Reinforcement Learning-Based CurrentControl of Permanent Magnet Synchronous MotorDrives for a Wide Range of Power Classes

A collection of Meta-Reinforcement Learning algorithms in PyTorch

Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)

Code repository for the paper Dif-MAML: Decentralized Multi-Agent Meta-Learning

Few-shot learing experiences using reinforcement learning and MAML

NLP sentiment analysis with MAML integration

Model Agnostic Meta Learning tested on Mixed Stock Prediction (MSP) and Free Pendulum environment (FPE) task

Machine Learning Force Field for Materials

Model Agnostic Meta Learner for Open AI Gym Retro Contest.

Training MAML algorithm and meta-learning techniques to predict the stock market.

Meta-Reinforcement Learning with Evolving Gradient Regularization

Game Theoretic Approach to MAML

李宏毅元学习笔记、MAML、meta learning有效原因

Implementing MAML using Ray to control IoT sensors