The Hebrew University of Jerusalem, Jerusalem, Israel.
PLoS Comput Biol. 2022 Nov 2;18(11):e1010664. doi: 10.1371/journal.pcbi.1010664. eCollection 2022 Nov.
Many decision-making studies have demonstrated that humans learn either expected values or relative preferences among choice options, yet little is known about what environmental conditions promote one strategy over the other. Here, we test the novel hypothesis that humans adapt the degree to which they form absolute values to the diversity of the learning environment. Since absolute values generalize better to new sets of options, we predicted that the more options a person learns about the more likely they would be to form absolute values. To test this, we designed a multi-day learning experiment comprising twenty learning sessions in which subjects chose among pairs of images each associated with a different probability of reward. We assessed the degree to which subjects formed absolute values and relative preferences by asking them to choose between images they learned about in separate sessions. We found that concurrently learning about more images within a session enhanced absolute-value, and suppressed relative-preference, learning. Conversely, cumulatively pitting each image against a larger number of other images across multiple sessions did not impact the form of learning. These results show that the way humans encode preferences is adapted to the diversity of experiences offered by the immediate learning context.
许多决策研究表明,人类学习的是选择选项的预期值或相对偏好,但对于什么环境条件促进一种策略而不是另一种策略知之甚少。在这里,我们检验了一个新颖的假设,即人类会根据学习环境的多样性来调整形成绝对价值的程度。由于绝对价值可以更好地推广到新的选项集,我们预测一个人学习的选项越多,他们就越有可能形成绝对价值。为了验证这一点,我们设计了一个为期多天的学习实验,由二十个学习阶段组成,每个阶段参与者在两组图像中进行选择,每组图像都与不同的奖励概率相关联。我们通过让参与者在单独的阶段中选择他们学习过的图像,来评估他们形成绝对价值和相对偏好的程度。我们发现,在一个阶段内同时学习更多的图像可以增强绝对价值学习,并抑制相对偏好学习。相反,在多个阶段中,将每张图像与更多的其他图像进行累计比较,并不会影响学习的形式。这些结果表明,人类编码偏好的方式适应了即时学习环境提供的多样性体验。