Adaptivity and efficiency in the design of sequential experiments

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Abstract/Contents

Abstract
Sequential experiments that take place in many practical settings are often characterized by an exploration-exploitation tradeoff that is captured by the multi-armed bandit framework. This framework has been studied extensively in the literature and applied in various application domains including revenue management, service operations, online retail, recommender systems, and healthcare. We study fundamental problems where there are uncertainties about key characteristics governing the sequential experimentation environment, such as the information acquisition process, the payoff structure, and the feedback structure. Furthermore, we design and analyze near-optimal dynamic optimization policies that are adaptive with respect to these characteristics.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2021; ©2021
Publication date 2021; 2021
Issuance monographic
Language English

Creators/Contributors

Author Momenisedei, Ahmadreza
Degree supervisor Gur, Yonatan
Thesis advisor Gur, Yonatan
Thesis advisor Boyd, Stephen P
Thesis advisor Lall, Sanjay
Thesis advisor Spiess, Jann
Thesis advisor Wager, Stefan
Degree committee member Boyd, Stephen P
Degree committee member Lall, Sanjay
Degree committee member Spiess, Jann
Degree committee member Wager, Stefan
Associated with Stanford University, Department of Electrical Engineering

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Ahmadreza Momeni.
Note Submitted to the Department of Electrical Engineering.
Thesis Thesis Ph.D. Stanford University 2021.
Location https://purl.stanford.edu/hs511rc0790

Access conditions

Copyright
© 2021 by Ahmadreza Momenisedei
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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