Information acquisition under resource limitations in a noisy environment

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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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APA

Soloviev, M., & Halpern, J. Y. (2018). Information acquisition under resource limitations in a noisy environment. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 6443–6450). AAAI press. https://doi.org/10.1609/aaai.v32i1.12122

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