Random Sampling of States in Dynamic Programming

Efficient sampling in approximate dynamic programming algorithms

Dynamic Programming (DP) is known to be a standard optimization tool for solving Stochastic Optimal Control (SOC) problems, either over a finite or an infinite horizon of stages. Under very general assumptions, commonly employed numerical algorithms are based on approximations of the cost-to-go functions, by means of suitable parametric models built from a set of sampling points in the d-dimens...

Cost Analysis of Acceptance Sampling Models Using Dynamic Programming and Bayesian Inference Considering Inspection Errors

Acceptance Sampling models have been widely applied in companies for the inspection and testing the raw material as well as the final products. A number of lots of the items are produced in a day in the industries so it may be impossible to inspect/test each item in a lot. The acceptance sampling models only provide the guarantee for the producer and consumer that the items in the lots are acco...

cost analysis of acceptance sampling models using dynamic programming and bayesian inference considering inspection errors

acceptance sampling models have been widely applied in companies for the inspection and testing the raw material as well as the final products. a number of lots of the items are produced in a day in the industries so it may be impossible to inspect/test each item in a lot. the acceptance sampling models only provide the guarantee for the producer and consumer that the items in the lots are acco...

Stochastic Dynamic Programming with Random Disturbances

Several peculiarities of stochastic dynamic programming problems where random vectors are observed before the decision is made at each stage are discussed in the first part of this paper. Surrogate problems are given for such problems with distance properties (for instance, transportation problems) in the second part.

Tutorial notes on Sampling Based Fitted Dynamic Programming Finite-Time Bounds for Sampling-Based Fitted Dynamic Programming