Bayesian Optimization With an Auxiliary Classifier for the Development of Polymer Materials

Tomoya Sasaki, Arisa Nakamura, Jun-Ichi Harasawa, Kazuo Hara, Ikumi Suzuki, Tatsuhiro Takahashi

Abstract: Recently, Bayesian optimization has become commonly used in material development. However, in the development of polymer materials, a problem occurs wherein polymers do not always get formed. To address this, we incorporated an auxiliary classifier into the flow of Bayesian optimization. The results of a preliminary experiment show the potential of this approach.