Skill Rating by Bayesian Inference

被引:17
作者
Di Fatta, Giuseppe [1 ]
Haworth, Guy McC. [1 ]
Regan, Kenneth W.
机构
[1] Univ Reading, Sch Syst Engn, Reading RG6 6AY, Berks, England
来源
2009 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DATA MINING | 2009年
关键词
KQKR;
D O I
10.1109/CIDM.2009.4938634
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:89 / 94
页数:6
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