Don't Stop 'Til You Get Enough: Adaptive Information Sampling in a Visuomotor Estimation Task

We investigated how subjects sample information in order to improve performance in a visuomotor estimation task. Subjects were rewarded for touching a hidden circular target based on visual cues to the target’s location. The cues were 'dots' drawn from a Gaussian distribution centered on the middle of the target. Subjects could sample as many cues as they wished, but the potential reward for hitting the target decreased by a fixed amount for each additional cue requested. The subjects' objective was to balance the benefits of increased information against the costs incurred in acquiring it. We compared human performance to ideal and found that subjects sampled more cues than dictated by the optimal stopping rule that tries to maximize expected gain. We contrast our results with recent reports in the literature that subjects typically under-sample.