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SIAMJO
2002
13 years 7 months ago
2002
In this paper we study a Monte Carlo simulation based approach to stochastic discrete optimization problems. The basic idea of such methods is that a random sample is generated and...
APPROX
2005
Springer
14 years 1 months ago
2005
Springer
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
UAI
1998
13 years 9 months ago
1998
This paper presents two new approaches to decomposing and solving large Markov decision problems (MDPs), a partial decoupling method and a complete decoupling method. In these app...
FLAIRS
2009
13 years 5 months ago
2009
Partially observable stochastic games (POSGs) provide a rich mathematical framework for planning under uncertainty by a group of agents. However, this modeling advantage comes wit...
SIAMNUM
2010
13 years 2 months ago
2010
Semidiscrete finite element approximation of the linear stochastic wave equation with additive noise is studied in a semigroup framework. Optimal error estimates for the determinis...