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Optimal Learning in the Laboratory Sciences

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Presentation on theme: "Optimal Learning in the Laboratory Sciences"— Presentation transcript:

1 Optimal Learning in the Laboratory Sciences
Tutorial: Optimal Learning in the Laboratory Sciences Understanding the objective function December 10, 2014 Warren B. Powell Kris Reyes Si Chen Princeton University Slide 1 1

2 Lecture outline Understanding the objective function
This section needs work © 2010 Warren B. Powell Slide 2

3 Objective Function Belief models describe our belief about the performance of an alternative (i.e. objective function) Different types of objective functions Performance metric (strength, length, quantity, …) Finding the best fit (learning the kinetic parameters) Utility function (mixing different objectives)

4 Performance metric Performance metric: maximizing the nanotube length, minimizing the number of nanotube defects, maximizing strength, maximizing the current generated, etc. Fe Ni PHN Al2O3+Fe Al2O3+Ni Nanotube Length

5 Finding the Best Fit Goodness of Fit and Residual Analysis
Mean square error Coefficient of determination (R2)

6 Utility Function Utility function: combination of multiple objective
Maximizing the nanotube length Minimize the number of defects Minimize experimental complexity Fe Ni PHN Al2O3+Fe Al2O3+Ni Nanotube Length Defects Courtesy

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