High Dimensional Decision Making, Upper and Lower Bounds

• Tác giả: Farzad Pourbabaee
• Ngôn ngữ: eng
• Ký hiệu phân loại: 003.56 Decision theory
• Thông tin xuất bản: 2021
• Bộ sưu tập: Báo, Tạp chí
• ID: 166880

Tóm tắt

A decision maker's utility depends on her action $a\in A \subset \mathbb{R}^d$ and the payoff relevant state of the world $\theta\in \Theta$. One can define the value of acquiring new information as the difference between the maximum expected utility pre- and post information acquisition. In this paper, I find asymptotic results on the expected value of information as $d \to \infty$, by using tools from the theory of (sub)-Guassian processes and generic chaining.