Depth, balancing, and limits of the Elo model


Much work has been devoted to the computational complexity of games. However, they are not necessarily relevant for estimating the complexity in human terms. Therefore, human-centered measures have been proposed, e.g. the depth. This paper discusses the depth of various games, extends it to a continuous measure. We provide new depth results and present tool (given-first-move, pie rule, size extension) for increasing it. We also use these measures for analyzing games and opening moves in Y, NoGo, Killall Go, and the effect of pie rules.

DOI: 10.1109/CIG.2015.7317964

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Showing 1-10 of 15 references

Darknight wins chinese dark chess tournament

  • S.-J Yen, J.-C Chen, B.-N Chen, W.-J Tseng
  • 2013
1 Excerpt

Overall review of the fide rating system

  • J Sonas
  • 2013

Mohex wins hex tournament

  • B Arneson, R Hayward, P Henderson
  • 2009
2 Excerpts