Bayesian inference with incomplete knowledge explains perceptual confidence and its deviations from accuracy
A Bayesian framework based on partially observable Markov decision processes (POMDPs) not only predicts subjects’ confidence in a perceptual decision making task but also explains well-known discrepancies between confidence and choice accuracy as arising from incomplete knowledge of the environment....
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2021
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/6022b29c2e3c48b6af4bb8f3daced477 |
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| Résumé: | A Bayesian framework based on partially observable Markov decision processes (POMDPs) not only predicts subjects’ confidence in a perceptual decision making task but also explains well-known discrepancies between confidence and choice accuracy as arising from incomplete knowledge of the environment. |
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