Improving Policy Functions in High-Dimensional Dynamic Games
收藏NBER2015-05-01 更新2025-01-04 收录
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https://www.nber.org/papers/w21124
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资源简介：
In this paper, we propose a method for finding policy function improvements for a single agent in high-dimensional Markov dynamic optimization problems, focusing in particular on dynamic games. Our approach combines ideas from literatures in Machine Learning and the econometric analysis of games to
提供机构：
美国国家经济研究局
创建时间：
2015-05-01
