Q-Learning 精解：从数学原理到代码实现的深度探索 | ApFramework
Jun 17, 2025 · 本文系统剖析Q-Learning算法的核心机制与理论基础，通过冰冻湖面环境的实例演示，从贝尔曼方程到代码实现，为读者构建强化学习的完整知识体系，助力AI学习之旅。
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).
深入解析强化学习之Q-Learning全攻略：理论基础、算法流程与应用实 …
通过这些步骤，Q-Learning算法能够学习在给定状态下采取哪些动作能够最大化长期累积奖励，而无需了解环境的具体动态。
RL-01:Q-Learning算法理解及实例应用 - CSDN博客
Jan 1, 2026 · Q-Learning是强化学习领域经典的无模型（Model-Free）时序差分（Temporal Difference，TD）学习算法，由Chris Watkins于1989年提出。 它的核心目标是学习动作价值函 …
Q-Learning 简介 - Hugging Face 深度强化学习课程 - Hugging Face 文档
**Q-Learning 是我们用来训练 Q 函数的算法**，它是一个**动作价值函数**，用于确定处于特定状态并在该状态下采取特定动作的价值。
深入浅出：Q-learning——强化学习的经典算法-百度开发者中心
Feb 17, 2024 · Q-learning是一种重要的强化学习算法，它通过构建一个Q表来学习状态-行为映射，实现智能体的决策。 本文将介绍Q-learning的基本原理、实现步骤以及应用场景，旨在帮助读者深入理解 …
强化学习详解：理论基础与核心算法解析 - 简书
Sep 26, 2024 · 本文详细介绍了强化学习的基础知识和基本算法，包括动态规划、蒙特卡洛方法和时序差分学习，解析了其核心概念、算法步骤及实现细节。 关注作者，复旦AI博士，分享AI领域全维度知 …
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 …
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.
What is q learning? - California Learning Resource Network
Jul 2, 2025 · Q-learning, a cornerstone of reinforcement learning (RL), provides a model-free approach to learning optimal control policies in Markov Decision Processes (MDPs).