Machine Learning-Based Experimental Design in Materials Science [chapter]

Thaer M. Dieb, Koji Tsuda
<span title="">2018</span> <i title="Springer Singapore"> Nanoinformatics </i> &nbsp;
In materials design and discovery processes, optimal experimental design (OED) algorithms are getting more popular. OED is often modeled as an optimization of a black-box function. In this chapter, we introduce two machine learningbased approaches for OED: Bayesian optimization (BO) and Monte Carlo tree search (MCTS). BO is based on a relatively complex machine learning model and has been proven effective in a number of materials design problems. MCTS is a simpler and more efficient approach
more &raquo; ... t showed significant success in the computer Go game. We discuss existing OED applications in materials science and discuss future directions.
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