Skill Rating by Bayesian Inference

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Di Fatta, G., Haworth, G. M. ORCID: https://orcid.org/0000-0001-9896-1448 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 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.

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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
Item Type	Book or Report Section
URI	https://reading-clone.eprints-hosting.org/id/eprint/4489
Identification Number/DOI	10.1109/CIDM.2009.4938634
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
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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Date Deposited:	17 Mar 2010 13:40	Date item deposited into CentAUR
Last Modified:	25 Jan 2024 03:43	Date item last modified

References

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