Depth, balancing, and limits of the Elo model

Marie-Liesse Cauwet; Olivier Teytaud; Hua-Min Liang; Shi-Jim Yen; Hung-Hsuan Lin; I-Chen Wu; Tristan Cazenave; Abdallah Saffidine

arXiv · 1511.02006

Depth, balancing, and limits of the Elo model

Marie-Liesse Cauwet·Olivier Teytaud·Hua-Min Liang·Shi-Jim Yen·Hung-Hsuan Lin·I-Chen Wu·Tristan Cazenave·Abdallah Saffidine

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Abstract

-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.

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BibTeX RIS

Marie-Liesse Cauwet, Olivier Teytaud, Hua-Min Liang, Shi-Jim Yen, Hung-Hsuan Lin, I-Chen Wu, Tristan Cazenave, Abdallah Saffidine. 2015-11-06. Depth, balancing, and limits of the Elo model. https://arxiv.org/abs/1511.02006

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