Precision-Adjustable Single-System Decision-Making

Much contemporary research on decision-making purports that the brain has two distinct systems which can be used: model-free or model-based. Model-free allows for fast and automatic choices, but with a higher likelihood of errors. Model-based allows for context-specific adaptability, but with greater cognitive computational costs.

In contrast to the prominent accounts of model-based vs model-free decision-making, I propose that the brain has a single decision system, which can be tuned to be more or less precise by investing more or less cognitive resources.

The degree of precision determines whether the system appears to be more ""model-free"" or more ""model-based"" for any given decision.

If successful, this project will play a critical role in redirecting a large sub-field of important decision-making (and learning) research. If unsuccessful, this project will provide powerful evidence that the current paradigm is correct.