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Here, we make use of Bayesian statistics to create a normative framework that automates an observation-inference-design loop to run "optimal" experiments which converge on a set of parameter values given a strong guiding model. 

Biological systems achieve dynamic functions at the macroscale through dissipative processes at the microscale, here we seek to learn the lessons of this distributed actuation mechanism to engineer efficient energy conversion for colloidal materials.