Q-learning - Wikipedia
Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring a model of the environment (model-free).
Q-Learning in Reinforcement Learning - GeeksforGeeks
Oct 31, 2025 · Q-Learning is a popular model-free reinforcement learning algorithm that helps an agent learn how to make the best decisions by interacting with its environment.
An Introduction to Q-Learning: A Tutorial For Beginners
Oct 27, 2022 · In this tutorial, we will learn about Q-learning and understand why we need Deep Q-learning. Moreover, we will learn to create and train Q-learning algorithms from scratch using Numpy …
Q-learning in its simplest form is dealing with discrete state and action spaces. In order to generalize to continuous state spaces, we need for function approximator that takes as input some vector …
What is q learning? - California Learning Resource Network
Jul 2, 2025 · This article delves into the mechanics of Q-learning, its underlying principles, implementation details, advantages, limitations, and future directions.
A Gentle Introduction to Q-Learning
Aug 5, 2025 · One of the most widely used algorithms in reinforcement learning is Q-learning, which examines how an agent learns the value of actions in different states without requiring a complete …
Q-Learning - an overview | ScienceDirect Topics
Q-learning is defined as a model-free reinforcement learning algorithm that estimates the expected future rewards of actions in given states using the Q-function, allowing for optimal policy learning …
Q-Learning Explained: Learn Reinforcement Learning Basics
Feb 14, 2026 · In this tutorial, we will explore the fundamental concepts of Q-learning, how it enables agents to make optimal decisions in various environments, and its role in the broader field of …
Q-Learning - ML Practical Knowledge Base
Q-Learning is a model-free, off-policy reinforcement learning (RL) algorithm that learns the value of an action in a particular state. It does not require a model of the environment (hence "model-free") and …
Introducing Q-Learning - Hugging Face Deep RL Course
Q-Learning is the algorithm we use to train our Q-function, an action-value function that determines the value of being at a particular state and taking a specific action at that state.