Probability weighting arises from boundary repulsions of cognitive noise
In both risky choice and perception, people overweight small and underweight large probabilities. While prospect theory models this with a probability weighting function, and Bayesian noisy coding mod...
π’ Preprint out! biorxiv.org/content/10.1... What gives rise to probability weighting, a cornerstone of Prospect Theory?
We show it comes from the natural boundedness of probabilities + cognitive noise. Adding boundaries adds multiple distortions, across risky choice & perception.
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But wouldn't the increase in performance go together with a decreased interpretability?
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CSC 2025
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Postdoc in the Litwin-Kumar lab at the Center for Theoretical Neuroscience at Columbia University.
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