Code_in_process's repositories
DeepRL-Agents
A set of Deep Reinforcement Learning Agents implemented in Tensorflow.
Electric-Vehicle-Route-Planning-on-Google-Map-Reinforcement-Learning
User can set up destination for any agent to navigate on Google Map and learn the best route for the agent based on its current condition and the traffic. Our result is 10% less energy consumption than the route provided by Google map
energy-market-deep-learning
Experiments in using deep learning to model competition in liberalised electricity markets.
ev_chargingcoordination2017
Optimal Scheduling of Electric Vehicle Charging in Distribution Networks
FleetSim
Event-based Simulation for Electric Vehicle Fleets
Hands-On-Reinforcement-Learning-With-Python
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
hems
Home Energy Management System for Small Prosumers Considering Electric Vehicle Load Scheduling
keras-rl
Deep Reinforcement Learning for Keras.
load_forecasts_attack
Code repo for E-Energy 2019 paper
Minecraft-Reinforcement-Learning
Deep Recurrent Q-Learning vs Deep Q Learning on a simple Partially Observable Markov Decision Process with Minecraft
PES-GM---Smart-Grid
Paper to be submitted for PES GM
pev_battery_charge
Battery charge management environment, designed as a multi-agent scenario with continuous observation and action space, where the agents are charging stations that must meet the energy requirements of a previously-scheduled group of PEVs (Plug-in Electric Vehicles), constrained to a local power supply restriction, and a global restriction from the containing Load Area.
pillar-theme
Pillar - Bootstrap 4 Resume/CV Theme for Developers
Reinforcement-Learning-2nd-Edition-by-Sutton-Exercise-Solutions
Solutions of Reinforcement Learning, An Introduction
Renewables_Scenario_Gen_GAN
The implementation of scenario generation for renewables production process
Resources-Allocation-in-The-Edge-Computing-Environment-Using-Reinforcement-Learning
Simulated the scenario between edge servers and users with a clear graphic interface. Also, implemented the continuous control with Deep Deterministic Policy Gradient (DDPG) to determine the resources allocation (offload targets, computational resources, migration bandwidth) in the edge servers
rlai-exercises
Exercise Solutions for Reinforcement Learning: An Introduction [2nd Edition]