论文标题
在嘈杂环境中资源限制下的信息获取
Information Acquisition Under Resource Limitations in a Noisy Environment
论文作者
论文摘要
我们在嘈杂环境中的资源限制下介绍了信息获取的理论模型。代理必须猜测给定布尔公式$φ$的真实价值在执行了公式中变量的真实值的数数噪声测试之后。我们观察到，总的来说，找到$ ϕ $的最佳测试策略的问题很难，但我们建议一种有用的启发式方法。我们使用的技术还可以洞悉两个显然是无关但有充分研究的问题：（1）\ emph {合理的注意力不集中}，也就是说，当忽略相关信息是合理的时（最佳策略可能涉及几乎涉及与$ $ ϕ $明显相关的测试变量，而不是$ ϕ $），并且（2）使得很难学习。
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) \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 $ϕ$), and (2) what makes a formula hard to learn/remember.
