Skill Rating by Bayesian Inference
Di Fatta, G., Haworth, G. M. and Regan, K. W. (2009) Skill Rating by Bayesian Inference. In: Computational Intelligence and Data Mining, 2009. CIDM '09. IEEE Symposium on. Institute of Electrical and Electronics Engineers , Los Alamitos, CA 90720-1264 USA, pp. 89-94. ISBN 9781424427659
To link to this article DOI: 10.1109/CIDM.2009.4938634
Systems Engineering often involves computer modelling the behaviour of proposed systems and their components. Where a component is human, fallibility must be modelled by a stochastic agent. The identification of a model of decision-making over quantifiable options is investigated using the game-domain of Chess. Bayesian methods are used to infer the distribution of players’ skill levels from the moves they play rather than from their competitive results. The approach is used on large sets of games by players across a broad FIDE Elo range, and is in principle applicable to any scenario where high-value decisions are being made under pressure.
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