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Skill Rating by Bayesian Inference

By Giuseppe Di Fatta, Guy McCrossan Haworth and Kenneth W Regan

Abstract

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

Publisher: Institute of Electrical and Electronics Engineers
Year: 2009
OAI identifier: oai:centaur.reading.ac.uk:4489

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