Deep Reinforcement Learning-based 2-level Tax Policy Optimization Simulation Environment Analysis and Experiment

Journal of Advanced Technology Research, Vol. 8, No. 2, pp. 9-13, Dec. 2023
10.11111/JATR.2023.8.2.009, Full Text:
Keywords: Tax Policy Optimization, Economic Simulation Analaysis, Reinforcement
Abstract

AI is actually developing steadily in many areas, but in particular, in the economic field, there are limited ways to experiment and evaluate policies through AI due to various environments and variables. In this paper, we used AI Economist, the Salesforce team's AI-based economic simulation environment, to analyze and experiment on a tax policy optimization simulation environment based on deep reinforcement learning for tax policy optimization through two-step learning between economic activity agents and government agents..


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Cite this article
[IEEE Style]
J. Heo, Y. Choi, Y. Han, "Deep Reinforcement Learning-based 2-level Tax Policy Optimization Simulation Environment Analysis and Experiment," Journal of Advanced Technology Research, vol. 8, no. 2, pp. 9-13, 2023. DOI: 10.11111/JATR.2023.8.2.009.

[ACM Style]
Joo-Seong Heo, Yo-Han Choi, and Youn-Hee Han. 2023. Deep Reinforcement Learning-based 2-level Tax Policy Optimization Simulation Environment Analysis and Experiment. Journal of Advanced Technology Research, 8, 2, (2023), 9-13. DOI: 10.11111/JATR.2023.8.2.009.