Abstract: This research article presents a comparison between two mainstream Deep Reinforcement Learning (DRL) algorithms, Asynchronous Advantage Actor-Critic (A3C) and Proximal Policy Optimization ...

keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seamlessly integrates with the deep learning library Keras. Furthermore, keras-rl works with OpenAI Gym ...

This repository contains an implementation of a Deep Reinforcement Learning (DRL) algorithm for managing the energy demand and supply of a microgrid. The implementation is built using Python and is ...

Abstract: An energy management system is crucial for optimizing the performance and reducing fuel consumption of Plug-in Hybrid Electric Vehicles (PHEVs), which plays an important role in sustainable ...

Reinforcement learning (RL) is a type of artificial intelligence. In RL, a system learns to make choices by interacting with its environment. This method involves experimentation. The system receives ...

The combustion process of boilers under deep peak shaving is a multivariate process which has complex characteristics such as super multivariability, being nonlinear, and large delay. It is difficult ...

Machines today can learn in highly advanced ways. Computers churn through billions of data points to rapidly detect complex patterns and solve real-world problems. How? By using machine learning ...