A Bayesian Framework for Modeling Confidence in Perceptual Decision Making A Bayesian Framework for Modeling Confidence in Perceptual Decision Making
Paper summary The authors' model confidence data from two experiments (conducted by others and previously published in the scientific literature) using a POMDP. In both experiments, subjects saw a random-dot kinematogram on each trial and made a binary choice about the dominant motion direction. The first experiment used monkeys as subjects and stimuli had a fixed duration. The second experiment used people as subjects and stimuli continued until a subject made a response. The paper reports that the POMDP model does a good job of fitting the experimental data, both the accuracy data and the confidence data.
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A Bayesian Framework for Modeling Confidence in Perceptual Decision Making
Khalvati, Koosha and Rao, Rajesh P.
Neural Information Processing Systems Conference - 2015 via Bibsonomy
Keywords: dblp


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