12.4 Decision Making Flashcards

1
Q

Normative decision theories

A

define how people ought to make decisions that yield the optimal choice. Very often, such theories fail to predict what people actually choose.

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2
Q

Descriptive decision theories

A

attempt to describe what people actually do, not what they should do.

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3
Q

action-outcome decisions

A

where the decisions involves some from of evaluation of the expected outcomes

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4
Q

stimulus-response decisions

A

if the outcome is consistent, it becomes a stimulus-response decision.

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5
Q

Model-based

A

means that the agent has an internal representation of some
aspect of the world and uses this model to evaluate different actions.

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6
Q

Model-free

A

means that you have only an input–output mapping, similar to
stimulus–response decisions.

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7
Q

primary reinforcers

A

they have a direct benefit for survival fitness

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8
Q

secondary reinforcers

A

sch as money and status, are rewards that have no intrinsic value themselves, but become rewarding through their association with other forms of reinforcement.

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9
Q

Value represented in the brain

A

in the ACC, anterior cingulate cortex, the LPFC and the OFC. Overall, the neurophysiological and neuroimaging studies indicate that the OFC plays a key role in the representation of value.

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10
Q

temporal discounting

A

is the observation that the value of a reward is reduced when we have to wait to receive that reward.

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11
Q

dopamine (DA).

A

Dopaminergic cells are scattered throughout the midbrain, sending axonal projections to many cortical and subcortical areas. Two of the primary loci of dopaminergic neurons are two brainstem nuclei, the substantia nigra pars compacta (SNc) and the ventral tegmental area (VTA).

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12
Q

Dopaminergic neurons that originate in the VTA project through two pathways:

A

The mesolimbic pathway travels to structures important to emotional processing, and the mesocortical pathway travels to the neocortex, particularly to the medial portions of the frontal lobe.

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13
Q

reward prediction error (RPE)

A

Rather than thinking of the spike in DA neuron activity as representing the reward, he suggested that it should be viewed as a reward prediction error (RPE), s the difference between the expected reward and what is actually obtained. The RPE is used as a learning signal to update value information as expectancies and the valence of rewards change. The activity of some DA neurons provides a neuronal
code of prediction errors.

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