Skill Rating by Bayesian Inference

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.

The Cold War in retrospect : 25 years after its end

This special issue of Cold War History offers a retrospective on the end of the Cold War, 25 years after its peaceful conclusion. This peaceful conclusion is an achievement that cannot be celebrated enough, and we must continue to build international relations in conflict and co-operation on this awareness of our common humanity and our common human fallibility.