Depth, balancing, and limits of the Elo model - Archive ouverte HAL
Communication Dans Un Congrès Année : 2015

Depth, balancing, and limits of the Elo model

Résumé

—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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Dates et versions

hal-01223116 , version 1 (05-11-2015)

Identifiants

Citer

Marie-Liesse Cauwet, Olivier Teytaud, Hua-Min Liang, Shi-Jim Yen, Hung-Hsuan Lin, et al.. Depth, balancing, and limits of the Elo model. IEEE Conference on Computational Intelligence and Games 2015, Aug 2015, Tainan, Taiwan. ⟨hal-01223116⟩
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