Bandit Problems under Censored Feedback
In this thesis, we study sequential decision-making models where the feedback received by the principal depends on strategic uncertainty (e.g., agents’ willingness to follow a recommendation) and/or random uncertainty (e.g., loss or delay in arrival of information). Such challenges often arise in AI...
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| Format: | Thesis |
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Massachusetts Institute of Technology
2023
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| Online Access: | https://hdl.handle.net/1721.1/147326 |