公开(公告)号：US20200027032A1

公开(公告)日：2020-01-23

申请号：US16039700

申请日：2018-07-19

申请人： INTERNATIONAL BUSINESS MACHINES CORPORATION

发明人： Tetsuro Morimura ,  Michiko Okudo ,  Takayuki Katsuki

IPC分类号： G06N99/00 ,  G06N7/08

摘要： A computer-implemented method for reducing computational costs for reducing computational costs to perform machine learning tasks includes generating one or more state partitioning candidates corresponding to a plurality of states associated with a partially observable Markov decision process (POMDP) model, determining that a given state partitioning candidate of the one or more state partitioning candidates satisfies a merge condition based on a state transition matrix for the given state partitioning candidate, and performing a machine learning task based on the POMDP model with merged states using the given state partitioning candidate.