Information Acquisition Under Resource Limitations in a Noisy Environment
Soloviev, Matvey, Halpern, Joseph Y.
–arXiv.org Artificial Intelligence
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 $\varphi$ 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 $\phi$ 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 $\phi$), and (2) what makes a formula hard to learn/remember.
arXiv.org Artificial Intelligence
May-20-2020
- Country:
- North America > United States > New York > Tompkins County > Ithaca (0.04)
- Genre:
- Research Report (0.64)