René's URL Explorer Experiment


Title: 强化学习论文浅读集合 | Keavnn'Blog

Open Graph Title: 强化学习论文浅读集合

X Title: 强化学习论文浅读集合

Description: 本文记录了一些粗读的强化学习相关的论文。

Open Graph Description: 本文记录了一些粗读的强化学习相关的论文。

X Description: 本文记录了一些粗读的强化学习相关的论文。

Keywords:

Mail addresses
oooooooooooooooocoo@vip.qq.com

Opengraph URL: http://StepNeverStop.github.io/rl-rough-reading.html

Generator: Hexo 3.8.0

direct link

Domain: stepneverstop.github.io

google-site-verificationzu-9nWphPjrzXV8v514mkHknIz4dNfHlib56-KNAu44
NoneKeavnn'Blog
theme-color#222
og:typearticle
og:site_nameKeavnn'Blog
og:localezh-Hans
og:imagehttp://stepneverstop.github.io/rl-rough-reading/MANet-structure.png
og:updated_time2020-04-11T04:00:03.946Z
twitter:cardsummary
twitter:imagehttp://stepneverstop.github.io/rl-rough-reading/gorila.png

Links:

https://github.com/StepNeverStop
Keavnn'Blog https://stepneverstop.github.io/
首页 https://stepneverstop.github.io/
关于 https://stepneverstop.github.io/about/
标签 https://stepneverstop.github.io/tags/
分类 https://stepneverstop.github.io/categories/
归档 https://stepneverstop.github.io/archives/
搜索 javascript:;
ReinforcementLearning https://stepneverstop.github.io/categories/ReinforcementLearning/
https://arxiv.org/pdf/1507.04296.pdfhttps://arxiv.org/pdf/1507.04296.pdf
https://stepneverstop.github.io/rl-rough-reading.html#模型示意图
https://stepneverstop.github.io/rl-rough-reading.html#特点
https://stepneverstop.github.io/rl-rough-reading.html#伪代码
https://stepneverstop.github.io/rl-rough-reading.html#稳定性
https://stepneverstop.github.io/rl-rough-reading.html#效果
https://arxiv.org/pdf/1809.05214.pdfhttps://arxiv.org/pdf/1809.05214.pdf
https://stepneverstop.github.io/rl-rough-reading.html#元强化学习
https://stepneverstop.github.io/rl-rough-reading.html#学习环境动态模型
https://stepneverstop.github.io/rl-rough-reading.html#基于环境动态模型的元强化学习
https://stepneverstop.github.io/rl-rough-reading.html#伪代码-1
https://stepneverstop.github.io/rl-rough-reading.html#流程示意图
https://stepneverstop.github.io/rl-rough-reading.html#效果-1
https://arxiv.org/pdf/1802.06070.pdfhttps://arxiv.org/pdf/1802.06070.pdf
https://sites.google.com/view/diayn/homehttps://sites.google.com/view/diayn/home
https://github.com/ben-eysenbach/sac/blob/master/DIAYN.mdhttps://github.com/ben-eysenbach/sac/blob/master/DIAYN.md
https://stepneverstop.github.io/rl-rough-reading.html#技能
https://stepneverstop.github.io/rl-rough-reading.html#亮点与作用
https://stepneverstop.github.io/rl-rough-reading.html#目标函数
《The IM Algorithm : A variational approach to Information Maximization》https://pdfs.semanticscholar.org/f586/4b47b1d848e4426319a8bb28efeeaf55a52a.pdf
https://stepneverstop.github.io/rl-rough-reading.html#伪代码-2
https://stepneverstop.github.io/rl-rough-reading.html#模型示意图-1
http://arxiv.org/abs/1906.04009http://arxiv.org/abs/1906.04009
https://github.com/BY571/Soft-Actor-Critic-and-Extensionshttps://github.com/BY571/Soft-Actor-Critic-and-Extensions
https://stepneverstop.github.io/rl-rough-reading.html#经验池逐渐缩放的原理
https://stepneverstop.github.io/rl-rough-reading.html#伪代码-3
https://stepneverstop.github.io/rl-rough-reading.html#优缺点
https://stepneverstop.github.io/rl-rough-reading.html#总结
http://arxiv.org/abs/1904.03367http://arxiv.org/abs/1904.03367
https://stepneverstop.github.io/rl-rough-reading.html#提出的方法
https://stepneverstop.github.io/rl-rough-reading.html#总结-1
http://arxiv.org/abs/1712.04603http://arxiv.org/abs/1712.04603
https://stepneverstop.github.io/rl-rough-reading.html#模型讲解
强化学习论文浅读集合https://stepneverstop.github.io/rl-rough-reading.html
Keavnnhttps://stepneverstop.github.io/
http://StepNeverStop.github.io/rl-rough-reading.htmlhttps://stepneverstop.github.io/rl-rough-reading.html
署名-非商业性使用-相同方式共享 4.0 国际https://creativecommons.org/licenses/by-nc-sa/4.0/
rlhttps://stepneverstop.github.io/tags/rl/
Universal Value Function Approximators https://stepneverstop.github.io/universal-value-function-approximators.html
Maximum Entropy-Regularized Multi-Goal Reinforcement-Learning https://stepneverstop.github.io/maximum-entropy-regularized-multi-goal-reinforcement-learning.html
51 日志 https://stepneverstop.github.io/archives/
11 分类 https://stepneverstop.github.io/categories/index.html
26 标签 https://stepneverstop.github.io/tags/index.html
RSS https://stepneverstop.github.io/atom.xml
GitHubhttps://github.com/StepNeverStop
https://creativecommons.org/licenses/by-nc-sa/4.0/
Fisher Changhttps://bluefisher.github.io
1. [DeepMind]Massively Parallel Methods for Deep Reinforcement Learning[Gorila]https://stepneverstop.github.io/rl-rough-reading.html#Gorila
1.1. 模型示意图https://stepneverstop.github.io/rl-rough-reading.html#模型示意图
1.2. 特点https://stepneverstop.github.io/rl-rough-reading.html#特点
1.3. 伪代码https://stepneverstop.github.io/rl-rough-reading.html#伪代码
1.4. 稳定性https://stepneverstop.github.io/rl-rough-reading.html#稳定性
1.5. 效果https://stepneverstop.github.io/rl-rough-reading.html#效果
2. [UCB/OpenAI]Model-Based Reinforcement Learning via Meta-Policy Optimization[MB-MPO]https://stepneverstop.github.io/rl-rough-reading.html#MB-MPO
2.1. 元强化学习https://stepneverstop.github.io/rl-rough-reading.html#元强化学习
2.2. 学习环境动态模型https://stepneverstop.github.io/rl-rough-reading.html#学习环境动态模型
2.3. 基于环境动态模型的元强化学习https://stepneverstop.github.io/rl-rough-reading.html#基于环境动态模型的元强化学习
2.4. 伪代码https://stepneverstop.github.io/rl-rough-reading.html#伪代码-1
2.5. 流程示意图https://stepneverstop.github.io/rl-rough-reading.html#流程示意图
2.6. 效果https://stepneverstop.github.io/rl-rough-reading.html#效果-1
3. [UCB/Google AI]Diversity is All Your Need: Learning Skills Without a Reward Function[DIAYN]https://stepneverstop.github.io/rl-rough-reading.html#DIAYN
3.1. 技能https://stepneverstop.github.io/rl-rough-reading.html#技能
3.2. 亮点与作用https://stepneverstop.github.io/rl-rough-reading.html#亮点与作用
3.3. 目标函数https://stepneverstop.github.io/rl-rough-reading.html#目标函数
3.4. 伪代码https://stepneverstop.github.io/rl-rough-reading.html#伪代码-2
3.5. 模型示意图https://stepneverstop.github.io/rl-rough-reading.html#模型示意图-1
4. Curiosity-Driven Experience Prioritization via Density Estimation[CDP]https://stepneverstop.github.io/rl-rough-reading.html#CDP
5. [Google]Continuous Deep Q-Learning with Model-based Acceleration[NAF]https://stepneverstop.github.io/rl-rough-reading.html#NAF
6. [NYU]Boosting Soft Actor-Critic: Emphasizing Recent Experience without Forgetting the Past[ERE]https://stepneverstop.github.io/rl-rough-reading.html#ERE
6.1. 经验池逐渐缩放的原理https://stepneverstop.github.io/rl-rough-reading.html#经验池逐渐缩放的原理
6.2. 伪代码https://stepneverstop.github.io/rl-rough-reading.html#伪代码-3
6.3. 优缺点https://stepneverstop.github.io/rl-rough-reading.html#优缺点
6.4. 总结https://stepneverstop.github.io/rl-rough-reading.html#总结
7. Reinforcement Learning with Attention that Works: A Self-Supervised Approachhttps://stepneverstop.github.io/rl-rough-reading.html#6SAN
7.1. 提出的方法https://stepneverstop.github.io/rl-rough-reading.html#提出的方法
7.2. 总结https://stepneverstop.github.io/rl-rough-reading.html#总结-1
8. [SNU]Multi-focus Attention Network for Efficient Deep Reinforcement Learning[MANet]https://stepneverstop.github.io/rl-rough-reading.html#MANet
8.1. 模型讲解https://stepneverstop.github.io/rl-rough-reading.html#模型讲解

Viewport: width=device-width, initial-scale=1, maximum-scale=1

URLs of crawlers that visited me.