AdaptiveBandit: A Multi-armed Bandit Framework for Adaptive Sampling in Molecular Simulations

• DOI: 10.1021/acs.jctc.0c00205
• Publication Date: 2020-06-15T16:43:17Z
• Authors: Adrià Pérez; Pablo Herrera-Nieto; Stefan Doerr; Gianni De Fabritiis
• Keywords: Adaptive sampling; Thompson Sampling; Folding (DSP implementation); Basis (linear algebra)

Sampling from the equilibrium distribution has always been a major problem in molecular simulations due to very high dimensionality of conformational space. Over several decades, many approaches have used overcome problem. In particular, we focus on unbiased simulation methods such as parallel and adaptive sampling. Here, recast sampling schemes basis multi-armed bandits develop novel algorithm under this framework, AdaptiveBandit. We test it multiple simplified potentials protein folding scenario. find that framework performs similarly or better than previous every type potential. Furthermore, provides new algorithms with asymptotic characteristics.