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Skill Rating by Bayesian Inference

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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

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To link to this article DOI: 10.1109/CIDM.2009.4938634

Abstract/Summary

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.

Item Type:Book or Report Section
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:4489
Uncontrolled Keywords:Bayes methods , behavioural sciences computing , decision making , mathematics computing , systems engineering Bayes methods , behavioural sciences computing , decision making , mathematics computing , systems engineering Bayes methods , behavioural sciences computing , decision making , mathematics computing , systems engineering Bayes methods , behavioural sciences computing , decision making , mathematics computing , systems engineering Bayes methods, behavioural science computing, decision making, mathematics computing, skill rating, stochastic agent, systems engineering,
Additional Information:This paper appears in: IEEE Symposium on Computational Intelligence and Data Mining, 2009. CIDM '09. March 30 2009-April 2 2009 Nashville, TN
Publisher:Institute of Electrical and Electronics Engineers

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