围棋的知识结构分析

Abstract

The potential implications of AlphaGo defeating a human player have not been fully discussed in the epistemological field. AlphaGo does not play in a nearly exhaustive way with a huge amount of computation, but has reached a higher level of “intuition” and “judgment”, which humans once thought was a difficult area for computer languages to break through. This phenomenon prompts us to rethink the structure of Go knowledge. From the perspective of epistemology, what kind of knowledge of Go is indeed reliable? Based on this fundamental question, this paper attempts to analyze the structure of Go knowledge. The main thought processes in the game of Go can be summarized as “intuition”, “calculation” and “judgement”, where rational deduction and empirical induction co-exist. In the past, the simple enumeration of knowledge points became the main focus of Go knowledge learning and teaching, now the nature of these knowledge points are distinguished, particularly the Go knowledge between“quantitative” and “non-quantitative”, moreover, the correlation between knowledge generation and both inherent human cognitive abilities and cognitive limits is presented. This paper analyzes the specific principles of how Go AI surpasses the human level of Go from the perspective of epistemology, provides theoretical support for how human players can leverage AI for new Go knowledge production in the future, and may serve as a bridge between Go and cognitive science research.