Deep Reinforcement Learning: Emerging Trends in Macroeconomics and Future Prospects
Author | : Tohid Atashbar |
Publisher | : International Monetary Fund |
Total Pages | : 32 |
Release | : 2022-12-16 |
ISBN-10 | : 9798400224713 |
ISBN-13 | : |
Rating | : 4/5 ( Downloads) |
Download or read book Deep Reinforcement Learning: Emerging Trends in Macroeconomics and Future Prospects written by Tohid Atashbar and published by International Monetary Fund. This book was released on 2022-12-16 with total page 32 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of Deep Reinforcement Learning (DRL) in economics has been an area of active research in recent years. A number of recent works have shown how deep reinforcement learning can be used to study a variety of economic problems, including optimal policy-making, game theory, and bounded rationality. In this paper, after a theoretical introduction to deep reinforcement learning and various DRL algorithms, we provide an overview of the literature on deep reinforcement learning in economics, with a focus on the main applications of deep reinforcement learning in macromodeling. Then, we analyze the potentials and limitations of deep reinforcement learning in macroeconomics and identify a number of issues that need to be addressed in order for deep reinforcement learning to be more widely used in macro modeling.