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Information sampling behavior with explicit sampling costs

机译:具有明确抽样成本的信息抽样行为

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摘要

The decision to gather information should take into account both the value of information and its accrual costs in time, energy and money. Here we explore how people balance the monetary costs and benefits of gathering additional information in a perceptual-motor estimation task. Participants were rewarded for touching a hidden circular target on a touch-screen display. The target’s center coincided with the mean of a circular Gaussian distribution from which participants could sample repeatedly. Each “cue” — sampled one at a time — was plotted as a dot on the display. Participants had to repeatedly decide, after sampling each cue, whether to stop sampling and attempt to touch the hidden target or continue sampling. Each additional cue increased the participants’ probability of successfully touching the hidden target but reduced their potential reward. Two experimental conditions differed in the initial reward associated with touching the hidden target and the fixed cost per cue. For each condition we computed the optimal number of cues that participants should sample, before taking action, to maximize expected gain. Contrary to recent claims that people gather less information than they objectively should before taking action, we found that participants over-sampled in one experimental condition, and did not significantly under- or over-sample in the other. Additionally, while the ideal observer model ignores the current sample dispersion, we found that participants used it to decide whether to stop sampling and take action or continue sampling, a possible consequence of imperfect learning of the underlying population dispersion across trials.
机译:收集信息的决定应同时考虑信息的价值及其在时间,精力和金钱上的应计成本。在这里,我们探索人们如何在感知运动估算任务中平衡货币成本和收集其他信息的收益。参与者因在触摸屏上触摸隐藏的圆形目标而获得奖励。目标的中心与圆形高斯分布的平均值重合,参与者可以从中重复采样。每个“提示”(一次采样一个)在屏幕上都绘制为一个点。在对每个提示进行采样之后,参与者不得不反复决定是否停止采样并尝试触摸隐藏的目标还是继续采样。每增加一个提示,都会增加参与者成功触摸隐藏目标的可能性,但会降低他们的潜在奖励。两种实验条件的不同之处在于,与触摸隐藏目标有关的初始报酬和每个提示的固定成本。对于每种情况,我们计算出参与者在采取行动之前应采样的最佳线索数量,以最大程度地提高预期收益。与最近的说法相反,即人们在采取行动之前所收集的信息少于客观地应该收集的信息,我们发现参与者在一种实验条件下被过度采样,而在另一种实验条件下没有明显过低或过采样。此外,尽管理想的观察者模型忽略了当前的样本分散,但我们发现参与者使用它来决定是停止取样,采取行动还是继续取样,这可能是整个试验中潜在人群分散学习不完善的可能结果。

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