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On Myopia in Rationally Inattentive Dynamic Information Acquisition
Arefanjazi, Hadis; Akyol, Emrah
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https://hdl.handle.net/2142/130301
Description
- Title
- On Myopia in Rationally Inattentive Dynamic Information Acquisition
- Author(s)
- Arefanjazi, Hadis
- Akyol, Emrah
- Issue Date
- 2025-09-17
- Keyword(s)
- Human–AI collaboration
- Dynamic information acquisition
- Rational inattention
- Majorization theory
- Matrix norms
- Abstract
- In many human–AI collaborative contexts, a decision maker must sequentially allocate limited attention to acquire information, culminating in a single decision at an exogenously determined time. The overall objective is to minimize a given function of the estimation error covariance at that final decision time. While the decision maker knows the current objective function, future objectives remain unspecified. Extending recent insights from economics on similar dynamic information acquisition problems, we use majorization theory to analyze conditions under which the optimal attention allocation exhibits monotonicity across time stages and remains time-consistent. Specifically, we characterize the conditions on the objective and attention functions that guarantee that a strategy chosen without full knowledge of future objectives remains optimal. Our results highlight the robustness of such allocation policies, offering guidelines for human–AI collaborations where partial or evolving knowledge of performance measures often characterizes the decision-making environment.
- Publisher
- Allerton Conference on Communication, Control, and Computing
- Series/Report Name or Number
- 2025 61st Allerton Conference on Communication, Control, and Computing Proceedings
- ISSN
- 2836-4503
- Type of Resource
- Text
- Genre of Resource
- Conference Paper/Presentation
- Language
- eng
- Handle URL
- https://hdl.handle.net/2142/130301&&
- Copyright and License Information
- Copyright 2025 is held by Hadis Arefanjazi and Emrah Akyol.
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61st Allerton Conference - 2025 PRIMARY
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