In this paper, we consider expected value, variance and worst-case optimization of nonlinear models. We present algorithms for computing optimal expected values, and variance, based on iterative Taylor expansions. We establish convergence and consider the relative merits of policies beaded on...

In this paper we discuss a basic framework for a grid computing market. It has long been argued that pricing of computer resources can act as a scheduling protocol. We take this idea to its natural conclusion by discussing the basic properties of such a model. We introduce agents that own...

Given a set of time series, it is of interest to discover subsets that share similar properties. For instance, this may be useful for identifying and estimating a single model that may fit conveniently several time series, instead of performing the usual identification and estimation steps for...

Analyses of global climate policy as a sequential decision under uncertainty have been severely restricted by dimensionality and computational burdens. Therefore, they have limited the number of decision stages, discrete actions, or number and type of uncertainties considered. In particular,...

Analyses of global climate policy as a sequential decision under uncertainty have been severely restricted by dimensionality and computational burdens. Therefore, they have limited the number of decision stages, discrete actions, or number and type of uncertainties considered. In particular, two...