2,554 research outputs found

    Intrinsic chess rating

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    This paper develops and tests formulas for representing playing strength at chess by the quality of moves played, rather than by the results of games. Intrinsic quality is estimated via evaluations given by computer chess programs run to high depth, ideally so that their playing strength is sufficiently far ahead of the best human players as to be a `relatively omniscient' guide. Several formulas, each having intrinsic skill parameters s for `sensitivity' and c for `consistency', are argued theoretically and tested by regression on large sets of tournament games played by humans of varying strength as measured by the internationally standard Elo rating system. This establishes a correspondence between Elo rating and the parameters. A smooth correspondence is shown between statistical results and the century points on the Elo scale, and ratings are shown to have stayed quite constant over time. That is, there has been little or no `rating inflation'. The theory and empirical results are transferable to other rational-choice settings in which the alternatives have well-defined utilities, but in which complexity and bounded information constrain the perception of the utility values

    The role of constraints in expert memory

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    A great deal of research has been devoted to developing process models of expert memory. However, K. J. Vicente and J. H. Wang (1998) proposed (a) that process theories do not provide an adequate account of expert recall in domains in which memory recall is a contrived task and (b) that a product theory, the constraint attunement hypothesis (CAH), has received a significant amount of empirical support. We compared 1 process theory (the template theory; TT; F. Gobet & H. A. Simon, 1996c) with the CAH in chess. Chess players (N = 36) differing widely in skill levels were required to recall briefly presented chess positions that were randomized in various ways. Consistent with TT, but inconsistent with the CAH, there was a significant skill effect in a condition in which both the location and distribution of the pieces were randomized. These and other results suggest that process models such as TT can provide a viable account of expert memory in chess

    Skilloscopy: Bayesian modeling of decision makers' skill

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    This paper proposes and demonstrates an approach, Skilloscopy, to the assessment of decision makers. In an increasingly sophisticated, connected and information-rich world, decision making is becoming both more important and more difficult. At the same time, modelling decision-making on computers is becoming more feasible and of interest, partly because the information-input to those decisions is increasingly on record. The aims of Skilloscopy are to rate and rank decision makers in a domain relative to each other: the aims do not include an analysis of why a decision is wrong or suboptimal, nor the modelling of the underlying cognitive process of making the decisions. In the proposed method a decision-maker is characterised by a probability distribution of their competence in choosing among quantifiable alternatives. This probability distribution is derived by classic Bayesian inference from a combination of prior belief and the evidence of the decisions. Thus, decision-makers’ skills may be better compared, rated and ranked. The proposed method is applied and evaluated in the gamedomain of Chess. A large set of games by players across a broad range of the World Chess Federation (FIDE) Elo ratings has been used to infer the distribution of players’ rating directly from the moves they play rather than from game outcomes. Demonstration applications address questions frequently asked by the Chess community regarding the stability of the Elo rating scale, the comparison of players of different eras and/or leagues, and controversial incidents possibly involving fraud. The method of Skilloscopy may be applied in any decision domain where the value of the decision-options can be quantified

    The e ects of gender-segregated competition on learning and performance in chess

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    A statistical analysis of FIDE rated games of high-performance chess players during a 10 year period is made. Players who finish with higher rating are found to have faced higher rating differences - their opponents are higher rated than them - and a positive correlation is found between challenge faced and rating improvement. Despite being a small minority in the population, women are found to play the majority of their games against other women. An agent-based model of chess tournament competition is presented incorporating the concept of desirable difficulties in which players get a long-term benefit from facing challenging opponents. Self-segregating to playing within a group to is found to be detrimental to the improvement of the elite of the group that self-segregates when they are a minority. The smaller the minority, the higher the performance cost found. This effect is found to be linked in the model to the learning that takes place when facing difficult opponents.#Competitividad1 recurso en línea (archivo de texto)Se realizó un análisis estadístico de partidas con rating FIDE de jugadores de ajedrez de alto desempeño durante 10 años. Se encontró que los jugadores que terminaron con mayor rating fueron quienes enfrentaron mayores diferencias de rating en su contra, comparados con sus oponentes, y se encontró una correlación positiva entre reto enfrentado en las partidas y mejoría de rating. A pesar de se una pequeña minoría en la población de jugadores, las mujeres juegan la mayor parte de sus partidas contra otras mujeres. Se presentó un modelo basado en agentes de la competición en torneos de ajedrez incorporando el concepto de dificultades deseables en el que los jugadores obtienen un beneficio a largo plazo al enfrentar oponentes retadores. Se encontró que auto-segregarse a jugar dentro de un grupo es perjudicial para la mejoría de rating de la élite del grupo que se auto-segrega. Se encontró que este efecto es mayor mientras menor sea la participación del grupo minoritario. Se halló que en el modelo este efecto se asocia al aprendizaje que ocurre cuando se enfrentan tareas retadoras

    Boltzmann and Fokker-Planck equations modelling the Elo rating system with learning effects

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    In this paper we propose and study a new kinetic rating model for a large number of players, which is motivated by the well-known Elo rating system. Each player is characterised by an intrinsic strength and a rating, which are both updated after each game. We state and analyse the respective Boltzmann type equation and derive the corresponding nonlinear, nonlocal Fokker-Planck equation. We investigate the existence of solutions to the Fokker-Planck equation and discuss their behaviour in the long time limit. Furthermore, we illustrate the dynamics of the Boltzmann and Fokker-Planck equation with various numerical experiments
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