Work

A Nonlinear Programming Method for Dynamic Programming

Year: 2016

Type: article

Abstract: A nonlinear programming formulation is introduced to solve infinite-horizon dynamic programming problems. This extends the linear approach to dynamic programming by using ideas from approximation theory to approximate value functions. Our numerical results show that this nonlinear programming is efficient and accurate, and avoids inefficient discretization.

Source: Macroeconomic Dynamics

DOI: 10.1017/s1365100515000528

Authors: Yongyang Cai, Kenneth L. Judd, Thomas S. Lontzek, Valentina Michelangeli, Che-Lin Su

Institutions: Hoover Institution, University of Chicago, University of Zurich, Bank of Italy

Language: English

Topic: Adaptive Dynamic Programming Control

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: National Science Foundation, Banca d'Italia

Award: DMUU: Center for Robust Decision Making on Climate and Energy Policy