508 search results - page 8 / 102 » Learning for stochastic dynamic programming |
ANOR
2006
13 years 11 months ago
2006
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...
NN
2006
Springer
13 years 10 months ago
2006
Springer
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
FLAIRS
1998
14 years 7 days ago
1998
Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
IOR
2008
13 years 11 months ago
2008
In 1958, Wagner and Whitin published a seminal paper on the deterministic uncapacitated lot-sizing problem, a fundamental model that is embedded in many practical production plann...
ICML
2006
IEEE
14 years 11 months ago
2006
IEEE
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...