This project aims to advance our understanding of the mechanisms responsible for the remarkable degree of autonomy— that is, genuinely self-determined behavior — of which humans are capable. Our work is guided by three fundamental premises: 1) Autonomous behavior relies on cognitive control; that is, the ability to evaluate and execute behavior determined by internally represented values and intentions. 2) There are tight constraints on the number of processes to which control can be allocated at any one time. 3) The mechanisms responsible for allocating control operate in a resource rational manner; that is, their function can be framed as a solution to the optimization problem of determining how to best allocate a limited resource (control), based on a cost-benefit evaluation of the available options. Our work will build on previous project work formalizing this approach as the Expected Value of Control (EVC) theory. The project will be organized into three focus areas. Focus Area A will address how agents learn representations of both the environment and its own behavior in ways that are shaped by the needs of control mechanisms. Focus Area B will address the operation of control mechanisms themselves, in particular with regard to their involvement in skill acquisition and planning. Focus Area C will address a question that is critical to our approach but has so far received little attention: How are the costs of control learned, and estimated when making control allocations? As in our previous work, we will pursue a tightly integrated program of theoretical and empirical work that draws equally from neuroscience, cognitive science, and computer science, all disciplines concerned with the mechanisms responsible for evaluation and control. We expect that this work will not only advance our understanding of the human ability for self-determined behavior — that is, autonomy — but also generate powerful new insights into how this can be improved.
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