A Comparison of the Belief-Adjustment Model and the Quantum Inference Model as Explanations of Order Effects in Human Inference


One of the oldest and most reliable findings regarding human inference is that the order of evidence affects the final judgment. These order effects are non-Bayesian by nature and are difficult to explain by classical probability models. We use the empirical results of two jury decision-making experiments to compare two different models of human belief updating: the belief-adjustment model and the quantum inference model. We also provide evidence to suggest the belief-adjustment model has limited predictive power when accounting for tasks involving extreme evidence whereas the quantum inference model does not.

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