ML Anthology

Information Acquisition Under Resource Limitations in a Noisy Environment

Matvey Soloviev, Joseph Y. Halpern
AAAI 2018 pp. 6443-6450
doi:10.1609/AAAI.V32I1.12122 /aaai/2018/soloviev2018aaai-information/

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 φ 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 φ is hard, but we suggest a useful heuristic. The techniques we use also give insight into two apparently unrelated, but well-studied problems: (1) rational inattention (the optimal strategy may involve hardly ever testing variables that are clearly relevant to φ) and (2) what makes a formula hard to learn/remember.

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Text

Soloviev and Halpern. "Information Acquisition Under Resource Limitations in a Noisy Environment." AAAI Conference on Artificial Intelligence, 2018. doi:10.1609/AAAI.V32I1.12122

Markdown

[Soloviev and Halpern. "Information Acquisition Under Resource Limitations in a Noisy Environment." AAAI Conference on Artificial Intelligence, 2018.](https://mlanthology.org/aaai/2018/soloviev2018aaai-information/) doi:10.1609/AAAI.V32I1.12122

BibTeX

@inproceedings{soloviev2018aaai-information,
  title     = {{Information Acquisition Under Resource Limitations in a Noisy Environment}},
  author    = {Soloviev, Matvey and Halpern, Joseph Y.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {6443-6450},
  doi       = {10.1609/AAAI.V32I1.12122},
  url       = {https://mlanthology.org/aaai/2018/soloviev2018aaai-information/}
}