Deep RL Bootcamp Lecture 4B Policy Gradients Revisited

阿新 • • 發佈：2018-05-01

pat https 分享 .com TP 9.png google ive hub

https://drive.google.com/file/d/0BxXI_RttTZAhTUpqUFdEZ3BXNFE/view

技術分享圖片

game of Pong is a MDP.

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終於一睹AK真容了，很有想法，很幽默

http://karpathy.github.io/

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Deep RL Bootcamp Lecture 4B Policy Gradients Revisited

pat https 分享 .com TP 9.png google ive hub https://drive.google.com/file/d/0BxXI_RttTZAhTUpqUFdEZ3BXNFE/view game of Pong is a MD

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spec incr any 9.png eal match sim AD tween in policy gradient, "a" is replaced by "u" usua

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add 分享 val acc ati ons width work rnn https://www.youtube.com/watch?v=fevMOp5TDQs

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圖片 ppr fit img UNC lin function ctu tin

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pac 分享圖片 previous ctu alt ram stuck parameter work you wouldn‘t try to explore any problem structure in DFO

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需要 clas 操作 -1 變換 png image cati fun 一些挑戰：網絡結構的選擇。CNN的想法是對鄰近的輸入，有著相同的weight。模型復雜度。最優化的初始點選擇。pre-training 計算復雜度。包含pre-training的DL框架

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來看 3.3 code ctu work pos component blog toe Lecture 13： Deep Learning 13.1 Deep Neural Network 13.2 Autoencoder 13.3 Denosing Autoenc

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width sam pythonic model var http ready efficient post CPU and GPU If you aren’t careful, training can bottleneck on reading dat

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png call inf learning 分享 eight deep min 技術 symmetric version: called Hopfield Net

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