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Increased monetary incentives enhance goal-directed reinforcement learning but fail to suppress automatic learning processes

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computational-modelingcomputational-neurosciencedecision-makinglearningquantitative-methodsreward
Adaptive reinforcement learning requires assigning outcomes to the features of actions that causally determine them. Yet humans also learn reward associations with action features that are explicitly known to be outcome-irrelevant, and these associations can bias subsequent choices. Whether such mal
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