We propose a new method for solving high-dimensional dynamic programming problems and recursive competitive equilibria with a large (but finite) number of heterogeneous agents using deep learning. We ...

Abstract: Reinforcement learning (RL) has roots in dynamic programming and it is called adaptive/approximate dynamic programming (ADP) within the control community. This paper reviews recent ...

<u>Dynamic programming</u> is an important algorithmic paradigm that breaks a problem into smaller subproblems and stores the solutions to avoid redundant computations, which optimizes performance. In ...

This primer is tailored for individuals new to macroeconomic policy analysis, including policymakers, economic analysts, and other professionals seeking to deepen their understanding of macroeconomic ...

Forbes contributors publish independent expert analyses and insights. Rachel Wells is a writer who covers leadership, AI, and upskilling. Regardless of your career choice, you will always need a ...

Learning to program in C on an online platform can provide structured learning and a certification to show along with your resume. Looking into learning C, one of the most popular programming ...

Abstract: In this article, an evolution-guided adaptive dynamic programming (EGADP) algorithm is developed to address the optimal regulation problems for the nonlinear systems. In the traditional ...

Ever book a flight and learn that other passengers on your aircraft paid wildly different fares for the exact same service? It’s not uncommon, thanks to a strategy called dynamic pricing, Dynamic ...