Exact(4)
The reinforcement model proposed predicts a learning process that takes the risk of the customer portfolio into account.
Following the reinforcement model an error is understood as a negative reinforcement signal processed within the mesencephalic dopaminergic system.
Under the reinforcement model, pre-mating isolation evolves in populations at risk of meeting heterospecific mates in order to avoid producing offspring of reduced fitness [4].
To examine whether risk was incorporated into the neuronal signals in a meaningful fashion consistent with expected utility theory and predicted by the modeling results, we examined dopamine responses to the same two gambles employed for the reinforcement model.
Similar(56)
The negative reinforcement model proposed here readily accounts for the absence of motion sickness in infants and toddlers, in that providing strong motivation to terminate aberrant motion does not make sense until a child is old enough to act on this motivation.
The negative reinforcement model of addiction would suggest that smokers may consume alcohol to relieve negative affective symptoms, such as those associated with MDD and withdrawal from nicotine.
The second series was used to check the accuracy of the modification suggested into minimum reinforcement model.
The biological reinforcement models [ 25] suggest that alcohol may alter neuroanatomical pathways that are involved in the positive reinforcement of internet use.
The reinforcement learning model fits to the behavioral data provide estimates of the reward prediction error experienced after every choice.
There are alternative theoretical approaches explaining modulations of the ERN: the error detection approach [33] and its extension, the reinforcement learning model [47].
The outcome onset was parametrically modulated by the prediction error as estimated by the reinforcement learning model.
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