Mastering the game of Go without human knowledge
These authors contributed equally to this work. The authors declare no competing financial interests. Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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論文翻譯：Mastering the Game of Go without Human Knowledge (第一部分)
將在 過程 methods 簡單的 能力 概率 通用 依靠 有著 長久以來，人工智能的一個目標是在那些具有挑戰性的領域實現超過人類表現的算法。最近，AlphaGo成為了在圍棋上第一個打敗了世界冠軍的程序。在AlphaGo中，使用深度神經網絡來進行樹搜索，評估位置，和選擇下一
Mastering the game of Go without human knowledge
These authors contributed equally to this work. The authors declare no competing financial interests. Publisher's note: Springer Nature remains neutral wit
Mastering the game of Go with deep neural networks and tree search
深度 策略 參數初始化 技術 以及 -1 簡單 cpu 網絡 Silver, David, et al. "Mastering the game of Go with deep neural networks and tree search." Nature 529.758
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用深度神經網路和樹搜尋征服圍棋 作者：David Silver 1 , Aja Huang 1 , Chris J. Maddison 1 , Arthur Guez 1 , Laurent Sifre 1 , George van den Driessche
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前言： 圍棋的英文是 the game of Go，標題翻譯為：《用深度神經網路和樹搜尋征服圍棋》。譯者簡介：大三，211，電腦科學與技術專業，平均分92分，專業第一。為了更好地翻譯此文，譯者查看了很多資料。譯者翻譯此論文已盡全力，不足之處希望讀者指出
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