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2018-01-14 上传大小:4.2MB
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DQN-《Human-level control through deep reinforcement learning》译文
Human-level control through deep reinforcement learning(中文翻译)
Paper reading: Human-level control through deep reinforcement learning
深度强化学习:入门(Deep Reinforcement Learning: Scratching the surface)
Human-level control through deep reinforcement learning 理解

Human-level control through deep reinforcement learning 理解

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Human-Level Control Through Deep Reinforcement Learning论文解读
深度强化学习(Deep Reinforcement Learning)入门:RL base & DQN-DDPG-A3C introduction
Paper reading —— Human-level control through deep reinforcement learning
深度强化学习(Deep Reinforcement Learning)的资源
笔记——“Human-level control through deep reinforcement learning”
[强化学习]区分Model-free和Model-based方法
论文笔记之:Human-level control through deep reinforcement learning
各种DQN
Paper Reading 2:Human-level control through deep reinforcement learning
Deep Q-Network,Nature-2015:Human-level control through deep reinforcement learning
Reinforcement Learning.pdf

This book is primarily based on a Machine Learning subset known as Reinforcement Learning. We cover the basics of Reinforcement Learning with the help of the Python programming language and touch on several aspects, such as Q learning, MDP, RL with Keras, and OpenAI Gym and OpenAI Environment, and a

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Deep Reinforcement Learning Hands-On pdf

This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep reinforcement learning (RL), from the first principles to the latest algorithms Evaluate high-profile RL methods, including value iteration, deep Q-networks, polic

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Reinforcement Learning.pdf(完美英文版)

We use Machine Learning to constantly improve the performance of machines or programs over time. The simplified way of implementing a process that improves machine performance with time is using Reinforcement Learning (RL). Reinforcement Learning is an approach through which intelligent programs, kn

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Deep Reinforcement Learning
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