Depth, balancing, and limits of the Elo model

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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Communication dans un congrès
IEEE Conference on Computational Intelligence and Games 2015, Aug 2015, Tainan, Taiwan. I, 2015
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https://hal.archives-ouvertes.fr/hal-01223116
Contributeur : Marie-Liesse Cauwet <>
Soumis le : jeudi 5 novembre 2015 - 21:50:42
Dernière modification le : vendredi 5 octobre 2018 - 10:06:59
Document(s) archivé(s) le : vendredi 28 avril 2017 - 04:51:06

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  • HAL Id : hal-01223116, version 1
  • ARXIV : 1511.02006

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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. I, 2015. 〈hal-01223116〉

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