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Discrete Mathematics
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Combinatorial games modeling seki in GO

Combinatorial games modeling seki in Go
Authors: Andrey Gol'berg; Vladimir Gurvich; Diogo Vieira Andrade; Konrad Borys; Gábor Rudolf;

Combinatorial games modeling seki in GO

Abstract

This paper describes results and conjectures on two closely related games, SEKI and D-SEKI, played on matrices of non-negative integers. These games were inspired of so-called seki positions in the game Go. This paper should be viewed as an investigation into the structure of SEKI and D-SEKI, without particular practical applications to Go. The two games are two-player turned-based perfect information partizan finite games which can end in a draw, so a priori there are nine possible outcome classes for SEKI and D-SEKI positions. Most of the paper consists of partial characterizations of the matrices that fall into particular outcome classes. The authors pay particular attention to the drawn matrices, called \textit{seki}, and single out among the seki the drawn matrices where each player has a unique non-losing move (\textit{complete seki}). The methods of the paper are combinatorial and elementary and the structure of the games seems interesting and pleasant. The paper contains four conjectures, three about complete seki and a fourth about seki, that seem amenable to both computer-aided brute force analysis and more mathematical methods.

Keywords

Go, combinatorial games, Combinatorial games, draw, pass, 2-person games, seki

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
hybrid