Deep reinforcement learning - Wikipedia
Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem of a computational agent learning to …
A Beginner's Guide to Deep Reinforcement Learning
Jul 23, 2025 · Agents are able to directly learn rules from sensory inputs thanks to DRL, which makes use of deep learning's ability to extract complex features from unstructured data. DRL relies heavily …
A Beginner's Guide to Deep Reinforcement Learning | Pathmind
Deep reinforcement learning combines artificial neural networks with a framework of reinforcement learning that helps software agents learn how to reach their goals. That is, it unites function …
Welcome to Spinning Up in Deep RL! — Spinning Up documentation
Imitation Learning and Inverse Reinforcement Learning 12. Reproducibility, Analysis, and Critique 13. Bonus: Classic Papers in RL Theory or Review Exercises Problem Set 1: Basics of Implementation …
[2412.05265] Reinforcement Learning: An Overview - arXiv.org
Dec 6, 2024 · View a PDF of the paper titled Reinforcement Learning: An Overview, by Kevin Murphy
Welcome to the Deep Reinforcement Learning Course - Hugging Face
Welcome to the most fascinating topic in Artificial Intelligence: Deep Reinforcement Learning. This course will teach you about Deep Reinforcement Learning from beginner to expert. It’s completely …
Deep Reinforcement Learning: A Chronological Overview and Methods
Feb 24, 2025 · Introduction: Deep reinforcement learning (deep RL) integrates the principles of reinforcement learning with deep neural networks, enabling agents to excel in diverse tasks ranging …
What Is Deep Reinforcement Learning? - Coursera
Dec 30, 2025 · Deep reinforcement learning is when a computer uses rewards and penalties to learn the next best action to achieve a specific goal. This process allows the computer to learn the same way …
Deep Reinforcement Learning: A Survey - IEEE Xplore
Sep 28, 2022 · Deep reinforcement learning (DRL) integrates the feature representation ability of deep learning with the decision-making ability of reinforcement learning so that it can achieve powerful end …
Deep Reinforcement Learning - Online Tutorials Library
Deep Reinforcement Learning uses artificial neural networks, which consist of layers of nodes that replicate the functioning of neurons in the human brain. These nodes process and relay information …