avkhimen/electric_vehicle_charging_simulation

This project implements Q-Learning to find the optimal policy for charging and discharging electric vehicles in a V2G scheme under conditions of uncertain commitment of EV owners. The problem is modelled as a multi-objective multi-agent cooperative game. Project is part of fulfillment criteria for ECE 730 course at the University of Alberta.

• 👋 Hi, I’m @avkhimen. I am a Canadian Engineer and Data Scientist.
• 👀 I’m interested in applications of Deep Learning, Deep Reinforcement Learning, and mathematical optimization methods to problems in transmission and distribution systems. I am also actively following developments in economics, finance, and cryptocurrencies.
• 🌱 I’m currently learning how to apply cutting-edge multi-agent reinforcement learning algorithms to problems involving continuous action spaces.
• 💞️ I’m looking to collaborate on solutions to problems in finance, cryptocurrencies, engineering, and social sciences.
• 📫 I can easily be reached at [email protected] or [email protected].

electric_vehicle_charging_simulation's Issues

Requrements in Readme

Hi Author, In the Requrements of the project's readme, you seem to have spelt argparse as argprase, not sure if this is a spelling error.