Acta Metallurgica Sinica(English letters) ›› 2008, Vol. 15 ›› Issue (1): 61-67.doi: 1005-8885 (2008) 01-0061-07

• Artificial Intelligence • 上一篇    下一篇

Automatic acquisition of pattern collocations in GO

刘知青;窦青   

  1. The School of Software Engineering, Beiging University of Posts and Telecommunications, Beiging 100876, China
  • 收稿日期:2006-12-20 修回日期:1900-01-01 出版日期:2008-03-31
  • 通讯作者: 刘知青

Automatic acquisition of pattern collocations in GO

  1. The School of Software Engineering, Beiging University of Posts and Telecommunications, Beiging 100876, China
  • Received:2006-12-20 Revised:1900-01-01 Online:2008-03-31
  • Contact: Liu Zhiqing

摘要:

The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial for successful GO playing. In a previous article of this subject, we have presented an algorithm for efficient and automatic acquisition of spatial patterns of GO as well as their frequency of occurrence from game records. In this article, we present two algorithms, one for efficient and automatic acquisition of pairs of spatial patterns that appear jointly in a local context, and the other for deter- mining whether the joint pattern appearances are of certain significance statistically and not just a coincidence. Results of the two algorithms include 1 779 966 pairs of spatial patterns acquired automatically from 16 067 game records of profess- sional GO players, of which about 99.8% are qualified as pattern collocations with a statistical confidence of 99.5% or higher.

关键词:

computer;games,;automatic;knowledge;acquisition,;spatial;patterns;recognition,;pattern;collocations

Abstract:

The quality, quantity, and consistency of the knowledge used in GO-playing programs often determine their strengths, and automatic acquisition of large amounts of high-quality and consistent GO knowledge is crucial for successful GO playing. In a previous article of this subject, we have presented an algorithm for efficient and automatic acquisition of spatial patterns of GO as well as their frequency of occurrence from game records. In this article, we present two algorithms, one for efficient and automatic acquisition of pairs of spatial patterns that appear jointly in a local context, and the other for deter- mining whether the joint pattern appearances are of certain significance statistically and not just a coincidence. Results of the two algorithms include 1 779 966 pairs of spatial patterns acquired automatically from 16 067 game records of profess- sional GO players, of which about 99.8% are qualified as pattern collocations with a statistical confidence of 99.5% or higher.

Key words:

computer games;automatic knowledge acquisition;spatial patterns recognition;pattern collocations

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