METHOD AND SYSTEM FOR IMPROVING A POLICY FOR A STOCHASTIC CONTROL PROBLEM

A method and system for improving a stochastic control problem policy, the method including a sampling device obtaining data representing sample Boltzmann machine configurations, obtaining a stochastic control problem's initialization data and initial policy; assigning representative data of initial coupler weights and node biases and the Boltzmann machine's transverse field strength to the sampling device; until a stopping criterion is met, generating a present-epoch state-action pair, amending, sampling for the present-epoch state-action pair, approximating a present-epoch state-action Q-function value, obtaining a future-epoch state-action pair through a stochastic state process including a stochastic optimization test on all state-action pairs to provide the action at the future-epoch and update the future-epoch state's policy; amending the representative data, sampling for the future-epoch state-action pair, obtaining a future-epoch state-action Q-function value, updating each weight and bias and providing the policy when the stopping criterion is met.