论文标题
通过的成本 - 使用深度学习AI扩大我们对古老游戏的理解
The cost of passing -- using deep learning AIs to expand our understanding of the ancient game of Go
论文作者
论文摘要
使用深度学习神经网络的AI发动机为分析传统棋盘游戏提供了出色的工具。在这里，我们有兴趣获得对古老游戏的新见解。为此，我们需要根据发动机的原始输出来定义新的数值度量。在本文中，我们开发了一种数值工具，用于以上下文敏感的方式和识别游戏功能自动移动性能评估。我们通过传递成本来衡量移动的紧迫性，这是石头当前配置和在同一董事会位置的假设传递之后的得分值差。在这里，我们研究了此措施的属性并描述了一些应用。
AI engines utilizing deep learning neural networks provide excellent tools for analyzing traditional board games. Here we are interested in gaining new insights into the ancient game of Go. For that purpose, we need to define new numerical measures based on the raw output of the engines. In this paper, we develop a numerical tool for automated move-by-move performance evaluation in a context-sensitive manner and for recognizing game features. We measure the urgency of a move by the cost of passing, which is the score value difference between the current configuration of stones and after a hypothetical pass in the same board position. Here we investigate the properties of this measure and describe some applications.
