强化学习算法解析：深度 Q 网络（Deep Q - Network，DQN）
Apr 16, 2025 · 深度 Q 网络（DQN）是强化学习与深度学习结合的一个重要里程碑，它通过将深度神经网络用于 Q 值函数的近似表示，解决了传统 Q-learning 在高维状态空间中的局限性。
DeepRL系列 (7): DQN (Deep Q-learning)算法原理与实现 - 知乎
其中DeepMind在第一篇中第一次提出Deep Reinforcement Learning（DRL）这个名称，并且提出DQN算法，实现从视频纯图像输入，完全通过Agent学习来玩Atari游戏的成果。
The Deep Q-Learning Algorithm - Hugging Face Deep RL Course
We learned that Deep Q-Learning uses a deep neural network to approximate the different Q-values for each possible action at a state (value-function estimation).
随着深度神经网络技术的不断发展,深度Q 网络(Deep Q-Networks,DQN )算法(Mnih et al., 2015)解决了这一问题,并点燃了深度强化学习的研究。 在本章中,我们将先回顾Q-Learning的背景。 之后介绍DQN …
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).
Deep Q-Learning in Reinforcement Learning - GeeksforGeeks
Oct 9, 2025 · Deep Q-Learning is a method that uses deep learning to help machines make decisions in complicated situations. It’s especially useful in environments where the number of possible situations …
Reinforcement Learning (DQN) Tutorial - PyTorch
This tutorial shows how to use PyTorch to train a Deep Q Learning (DQN) agent on the CartPole-v1 task from Gymnasium. You might find it helpful to read the original Deep Q Learning (DQN) paper
强化学习 7—— 一文读懂 Deep Q-Learning（DQN）算法_deep q learning …
在 DQN 中也是这样解决的，有两套一样的网络，分别是 Q estimation 网络和 Q Target 网络。 要做的就是固定住 Q target 网络，那如何固定呢？ 比如可以让 Q estimation 网路训练10次，然后把 Q …
Deep Q-Learning Tutorial: minDQN - Towards Data Science
Nov 18, 2020 · Critically, Deep Q-Learning replaces the regular Q-table with a neural network. Rather than mapping a state-action pair to a q-value, a neural network maps input states to (action, Q-value) …
Deep Q-Networks (DQN) - Online Tutorials Library
A Deep Q-Network (DQN) is an algorithm in the field of reinforcement learning. It is a combination of deep neural networks and Q-learning, enabling agents to learn optimal policies in complex …