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Found 9 papers, 0 papers with code
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation
We derive the theoretical relationship between DBM and EXP, and show that EXP gains computational efficiency by foregoing the representation of inferential uncertainty (as does the delta rule), but that it nevertheless achieves near-Bayesian performance due to its ability to incorporate a "persistent prior" influence unique to DBM and absent from the other algorithms.
Why so gloomy? A Bayesian explanation of human pessimism bias in the multi-armed bandit task
We find that the "pessimism bias" in the bandit task is well captured by the prior mean of DBM when fitted to human choices; but it is poorly captured by the prior mean of the Fixed Belief Model (FBM), an alternative Bayesian model that (correctly) assumes reward rates to be constants.
Beauty-in-averageness and its contextual modulations: A Bayesian statistical account
This statistical coding cost account explains both BiA, where facial blends generally have higher likelihood than ``parent faces'', and UiA, when the preceding context or task restricts face representation to a task-relevant subset of features, thus redefining statistical typicality and encoding cost within that subspace.
Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting
We compare human behavior to a variety of models that vary in their representational and computational complexity.
Context-sensitive active sensing in humans
Humans and animals readily utilize active sensing, or the use of self-motion, to focus sensory and cognitive resources on the behaviorally most relevant stimuli and events in the environment.
Active Sensing as Bayes-Optimal Sequential Decision Making
Sensory inference under conditions of uncertainty is a major problem in both machine learning and computational neuroscience.
Strategic Impatience in Go/NoGo versus Forced-Choice Decision-Making
We postulate that this ``impatience'' to go is a strategic adjustment in response to the implicit asymmetry in the cost structure of GNG: the NoGo response requires waiting until the response deadline, while a Go response immediately terminates the current trial.
A rational decision making framework for inhibitory control
Intelligent agents are often faced with the need to choose actions with uncertain consequences, and to modify those actions according to ongoing sensory processing and changing task demands.
Sequential effects: Superstition or rational behavior?
In a variety of behavioral tasks, subjects exhibit an automatic and apparently sub-optimal sequential effect: they respond more rapidly and accurately to a stimulus if it reinforces a local pattern in stimulus history, such as a string of repetitions or alternations, compared to when it violates such a pattern.
