Learning the fundamentals in a stationary environment

• 成果类型: Article
• 署名作者: Al-Najjar, Nabil I.; Shmaya, Eran
• 署名单位: Northwestern University
• 刊物名称: GAMES AND ECONOMIC BEHAVIOR
• ISSN/ISSBN: 0899-8256
• DOI: 10.1016/j.geb.2018.02.007
• 发表日期: 2018
• 页码: 616-624
• 关键词: Learning; Merging; stationarity

摘要

A Bayesian agent relies on past observations to learn the structure of a stationary process. We show that the agent's predictions about near-horizon events become arbitrarily close to those he would have made if he knew the long-run empirical frequencies of the process. (C) 2018 Elsevier Inc. All rights reserved.