In times of rapid macroeconomic change it would seem useful for both fiscal and monetary policy to be modified frequently. This is true for monetary policy with monthly meetings of the Open Market Committee. It is not true for fiscal policy which mostly varies with the annual Congressional...

<Para ID="Par1">Sometimes, the feasible set of an optimization problem that one aims to solve using a Nonlinear Programming algorithm is empty. In this case, two characteristics of the algorithm are desirable. On the one hand, the algorithm should converge to a minimizer of some infeasibility measure. On the...</para>

This chapter of the Handbook of Computational Economics is mostly about research on active learning and is confined to discussion of learning in dynamic models in which the systems equations are linear, the criterion function is quadratic and the additive noise terms are Gaussian. Though there...

In this paper we turn our attention to comparing the policy function obtained by Beck and Wieland (2002) to the one obtained with adaptive control methods. It is an integral part of the optimal learning method used by Beck and Wieland to obtain a policy function that provides the optimal control...

In a recent paper, Birgin, Floudas and Martínez introduced an augmented Lagrangian method for global optimization. In their approach, augmented Lagrangian subproblems are solved using the <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\alpha $$</EquationSource> </InlineEquation> <Emphasis Type="SmallCaps">BB method and convergence to global minimizers was obtained assuming feasibility of the...</emphasis></equationsource></inlineequation>

In this paper we turn our attention to comparing the policy function obtained by Beck and Wieland (J Econ Dyn Control 26:1359–1377, <CitationRef CitationID="CR6">2002</CitationRef>) to the one obtained with adaptive control methods. It is an integral part of the optimal learning method used by Beck and Wieland to obtain a policy...</citationref>

This chapter of the Handbook of Computational Economics is mostly about research on active learning and is confined to discussion of learning in dynamic models in which the system equations are linear, the criterion function is quadratic, and the additive noise terms are Gaussian. Though there...