📄️ Reinforcement Learning
Reinforcement Learning (RL): an agent learns to make decisions by interacting with an environment. The goal of the agent is to take actions that maximize a cumulative reward.
📄️ Deep Reinforcement Learning
Deep Reinforcement Learning (DRL) is a subfield of RL that uses deep neural networks to solve more complex problems. In traditional RL, the states and actions are often represented in a simple table. However, this approach becomes impractical for problems with a vast number of states, such as a game of chess or a self-driving car navigating a city.
📄️ Deep Reinforcement Learning (DRL) Course by HuggingFace
RL_Basics
📄️ DRL for optimal DER scheduling (AI EMS)
DRL in AI EMS for Optimal DER Scheduling