Acquisition of decision making criteria: reward rate ultimately beats accuracy
Acquisition of decision making criteria: reward rate ultimately beats accuracy
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DOI：
10.3758/s13414-010-0049-7
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发表时间：
2011-02-01
影响因子：
1.7
通讯作者：
Cohen, Jonathan D.
中科院分区：
文献类型：
--
作者：
Balci, Fuat;Simen, Patrick;Cohen, Jonathan D.
在许多决策任务中，速度和准确性之间的权衡极大地影响了获得奖励的比率。先前的报告表明，人类参与者在单次会话、两种选择的强制选择任务中，往往采用次优的速度和准确性权衡。我们调查了人类是否获得最佳的速度和精度权衡时，广泛训练与多种信号质量。当表现以决策时间和准确性为特征时，我们的参与者最终在高信号质量的情况下表现得几乎是最佳的。参与者没有采用对每个信号质量单独最优的决策标准，而是采用了对大多数信号质量几乎最优的单一阈值。然而，为不同的连贯条件设置一个单一的阈值只会导致最大可能奖励率的下降可以忽略不计。最后，我们测试了关于次优表现可能来源的两个假设：(1)偏爱准确度而不是奖励率；(2)由于时间不确定性而错误估计奖励率。我们的研究结果为这两个假设提供了支持，同时也为参与者可以学会接近最优的假设提供了支持。我们特别发现，准确性偏差在早期表现中占主导地位，但随着练习大大减少。最优性能与观测性能之间的残差可以用时间估计中对不确定性的自适应响应来解释。
Speed-accuracy trade-offs strongly influence the rate of reward that can be earned in many decision-making tasks. Previous reports suggest that human participants often adopt suboptimal speed-accuracy trade-offs in single session, two-alternative forced-choice tasks. We investigated whether humans acquired optimal speed-accuracy trade-offs when extensively trained with multiple signal qualities. When performance was characterized in terms of decision time and accuracy, our participants eventually performed nearly optimally in the case of higher signal qualities. Rather than adopting decision criteria that were individually optimal for each signal quality, participants adopted a single threshold that was nearly optimal for most signal qualities. However, setting a single threshold for different coherence conditions resulted in only negligible decrements in the maximum possible reward rate. Finally, we tested two hypotheses regarding the possible sources of suboptimal performance: (1) favoring accuracy over reward rate and (2) misestimating the reward rate due to timing uncertainty. Our findings provide support for both hypotheses, but also for the hypothesis that participants can learn to approach optimality. We find specifically that an accuracy bias dominates early performance, but diminishes greatly with practice. The residual discrepancy between optimal and observed performance can be explained by an adaptive response to uncertainty in time estimation.