From household appliances to applications in robotics, engineered systems involving
complex dynamics can only be as effective as the algorithms that control them. While …

This is a thoroughly updated edition of Dynamic Asset Pricing Theory, the standard text for
doctoral students and researchers on the theory of asset pricing and portfolio selection in …

This chapter provides an overview of solution and estimation techniques for dynamic
stochastic general equilibrium models. We cover the foundations of numerical …

Structural Macroeconometrics provides a thorough overview and in-depth exploration of
methodologies, models, and techniques used to analyze forces shaping national …

This paper compares solution methods for dynamic equilibrium economies. We compute
and simulate the stochastic neoclassical growth model with leisure choice using first …

This paper presents a new approach to solve dynamic decision models in economics. The
proposed procedure, called Nonlinear Model Predictive Control (NMPC), relies on the …

This chapter is concerned with numerical simulation of dynamic economic models. We focus
on some basic algorithms and assess their accuracy and stability properties. This analysis is …

This paper extends Carroll's [2005. The method of endogenous gridpoints for solving
dynamic stochastic optimization problems. National Bureau of Economic Research …

Reinforcement Learning (RL) is a widely employed machine learning architecture that has
been applied to a variety of control problems. However, applications in safety-critical …

The study of the solutions of dynamic models with optimizing agents has often been limited
by a lack of available analytical techniques to explicitly find the global solution paths. On the …