在用深度神经网络和树搜索掌握围棋游戏的论文中，AlphaGo 网络的输入特征包含一个常量平面和一个常量零平面，如下所示。

Feature       #of planes Description 
Stone colour  3          Player stone/opponent stone/empty 
Ones          1          A constant plane filled with 1 
Turns since   8          How many turns since a move was played 
Liberties     8          Number of liberties (empty adjacent points) 
Capture size  8          How many opponent stones would be captured 
Self-atari size 8        How many of own stones would be captured 
Liberties after move 8   Number of liberties after this move is played 
Ladder capture 1         Whether a move at this point is a successful ladder capture 
Ladder escape 1          Whether a move at this point is a successful ladder escape 
Sensibleness  1          Whether a move is legal and does not fill its own eyes 
Zeros         1          A constant plane filled with 0 
Player color  1          Whether current player is black

我想知道为什么这些特征是必要的，因为我认为恒定平面不包含任何信息，它会使网络变得更大，因此更难训练。

更何况我看不懂这里的尖锐标志。是“数”的意思吗？但是一个数字就足以代表“自下棋以来的转数”，为什么是八？

非常感谢你。