On the Impact of Bounded Rationality in Strategic Data Gathering

Fuente: arXiv
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Autores principales: Anand, Anju, Akyol, Emrah
Formato: Preprint
Publicado: 2024
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author Anand, Anju
Akyol, Emrah
author_facet Anand, Anju
Akyol, Emrah
contents We consider the problem of estimation from survey data gathered from strategic and boundedly-rational agents with heterogeneous objectives and available information. Particularly, we consider a setting where there are three different types of survey responders with varying levels of available information, strategicness, and cognitive hierarchy: i) a non-strategic agent with an honest response, ii) a strategic agent that believes everyone else is a non-strategic agent and that the decoder also believes the same, hence assumes a naive estimator, i.e., level-1 in cognitive hierarchy, iii) and strategic agent that believes the population is Poisson distributed over the previous types, and that the decoder believes the same. We model each of these scenarios as a strategic classification of a 2-dimensional source (possibly correlated source and bias components) with quadratic distortion measures and provide a design algorithm. Finally, we provide our numerical results and the code to obtain them for research purposes at https://github.com/strategic-quantization/bounded-rationality.
format Preprint
id arxiv_https___arxiv_org_abs_2409_13845
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle On the Impact of Bounded Rationality in Strategic Data Gathering
Anand, Anju
Akyol, Emrah
Computer Science and Game Theory
Systems and Control
We consider the problem of estimation from survey data gathered from strategic and boundedly-rational agents with heterogeneous objectives and available information. Particularly, we consider a setting where there are three different types of survey responders with varying levels of available information, strategicness, and cognitive hierarchy: i) a non-strategic agent with an honest response, ii) a strategic agent that believes everyone else is a non-strategic agent and that the decoder also believes the same, hence assumes a naive estimator, i.e., level-1 in cognitive hierarchy, iii) and strategic agent that believes the population is Poisson distributed over the previous types, and that the decoder believes the same. We model each of these scenarios as a strategic classification of a 2-dimensional source (possibly correlated source and bias components) with quadratic distortion measures and provide a design algorithm. Finally, we provide our numerical results and the code to obtain them for research purposes at https://github.com/strategic-quantization/bounded-rationality.
title On the Impact of Bounded Rationality in Strategic Data Gathering
topic Computer Science and Game Theory
Systems and Control
url https://arxiv.org/abs/2409.13845