Information Acquisition Under Resource Limitations in a Noisy Environment
Abstract
We introduce a theoretical model of information acquisition under resource limitations in a noisy environment. An agent must guess the truth value of a given Boolean formula after performing a bounded number of noisy tests of the truth values of variables in the formula. We observe that, in general, the problem of finding an optimal testing strategy for is hard, but we suggest a useful heuristic. The techniques we use also give insight into two apparently unrelated, but well-studied problems: (1) \emph{rational inattention}, that is, when it is rational to ignore pertinent information (the optimal strategy may involve hardly ever testing variables that are clearly relevant to ), and (2) what makes a formula hard to learn/remember.
Cite
@article{arxiv.2005.10383,
title = {Information Acquisition Under Resource Limitations in a Noisy Environment},
author = {Matvey Soloviev and Joseph Y. Halpern},
journal= {arXiv preprint arXiv:2005.10383},
year = {2020}
}
Comments
A preliminary version of the paper appeared in \emph{Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)}, 2018