2,468 research outputs found

    Computer Shogi 2000 through 2004

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    Spartan Daily, December 5, 1980

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    Volume 75, Issue 66https://scholarworks.sjsu.edu/spartandaily/6701/thumbnail.jp

    Ranking in Swiss system chess team tournaments

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    The paper uses paired comparison-based scoring procedures for ranking the participants of a Swiss system chess team tournament. We present the main challenges of ranking in Swiss system, the features of individual and team competitions as well as the failures of official lexicographical orders. The tournament is represented as a ranking problem, our model is discussed with respect to the properties of the score, generalized row sum and least squares methods. The proposed procedure is illustrated with a detailed analysis of the two recent chess team European championships. Final rankings are compared by their distances and visualized with multidimensional scaling (MDS). Differences to official ranking are revealed by the decomposition of least squares method. Rankings are evaluated by prediction accuracy, retrodictive performance, and stability. The paper argues for the use of least squares method with a results matrix favoring match points

    v. 57, no. 25, November 30, 1989

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    Spartan Daily, December 9, 1980

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    Volume 75, Issue 68https://scholarworks.sjsu.edu/spartandaily/6703/thumbnail.jp

    1998 Modulus

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    1998 Yearbook for Rose-Hulman Institute of Technology Terre Haute, IN 47803https://scholar.rose-hulman.edu/modulus/1079/thumbnail.jp

    The Queen's Gambit : Explaining the superstar effect using evidence from chess

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    Superstars exist in classrooms and workplaces. Superstars can intimidate others and create a negative performance shock, or they can encourage others by inspiring everybody to “step up their game.” In this study, we examine two effects: the impact of head-to-head competition with a superstar (direct) effect and the influence of a superstar presence on players' performance (indirect) effect. We find that the direct superstar effect in theory and in the data is always negative. The indirect superstar effect is neutral in theory, but depends on the intensity of the superstar in the data: if the skill gap between the superstar and the rest is small (large), there is a positive (negative) indirect effect
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