In this paper we derive estimates of the sample sizes required to solve a multistage stochastic programming problem with a given accuracy by the (conditional sampling) sample aver...
The paper discusses simple functional constraint networks and a value propagation method for program construction. Structural synthesis of programs is described as an example of d...
Abstract. We present experimental results about learning function values (i.e. Bellman values) in stochastic dynamic programming (SDP). All results come from openDP (opendp.sourcef...
—Since many embedded systems execute a predefined set of programs, tuning system components to application programs and data is the approach chosen by many design techniques to o...
To solve a decision problem under uncertainty via stochastic programming means to choose or to build a suitable stochastic programming model taking into account the nature of the r...