TIMCkai's Stars
openai/multiagent-particle-envs
Code for a multi-agent particle environment used in the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments"
starry-sky6688/MADDPG
Pytorch implementation of the MARL algorithm, MADDPG, which correspondings to the paper "Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environments".
zhining-lu/netty-quic-proxy
A forward proxy base netty uses quic protocol
jaromiru/AI-blog
Accompanying repository for Let's make a DQN / A3C series.
ljpzzz/machinelearning
My blogs and code for machine learning. http://cnblogs.com/pinard
microsoft/nni
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
yanchang-liang/agent-based-modeling-in-electricity-market-using-DDPG-algorithm
Agent-Based Modeling in Electricity Market Using Deep Deterministic Policy Gradient Algorithm
MorvanZhou/Reinforcement-learning-with-tensorflow
Simple Reinforcement learning tutorials, 莫烦Python 中文AI教学
tahanakabi/DRL-for-microgrid-energy-management
We study the performance of various deep reinforcement learning algorithms for the problem of microgrid’s energy management system. We propose a novel microgrid model that consists of a wind turbine generator, an energy storage system, a population of thermostatically controlled loads, a population of price-responsive loads, and a connection to the main grid. The proposed energy management system is designed to coordinate between the different sources of flexibility by defining the priority resources, the direct demand control signals and the electricity prices. Seven deep reinforcement learning algorithms are implemented and empirically compared in this paper. The numerical results show a significant difference between the different deep reinforcement learning algorithms in their ability to converge to optimal policies. By adding an experience replay and a second semi-deterministic training phase to the well-known Asynchronous advantage actor critic algorithm, we achieved considerably better performance and converged to superior policies in terms of energy efficiency and economic value.
datawhalechina/easy-rl
强化学习中文教程（蘑菇书🍄），在线阅读地址：https://datawhalechina.github.io/easy-rl/
Yifeng-He/Optimal-Scheduling-for-Charging-and-Discharging-of-Electric-Vehicles
This project develops an optimal scheduling algorithm to minimize the total cost for charging and discharging of electric vehicles.
fneum/ev_chargingcoordination2017
Optimal Scheduling of Electric Vehicle Charging in Distribution Networks
FZJ-IEK3-VSA/FINE
The FINE python package provides a framework for modeling, optimizing and assessing energy systems
FZJ-IEK3-VSA/RESKit
A toolkit to help generate renewable energy generation time-series for energy systems analysis
hugorcf/Renewable-energy-weather
OpenEnergyPlatform/ontology
Repository for the Open Energy Ontology (OEO)