Department of Social Psychology, The University of Tokyo, Tokyo, 113-0033, Japan.
Japan Society for the Promotion of Science, Tokyo, 102-0083, Japan.
Sci Rep. 2022 May 16;12(1):8047. doi: 10.1038/s41598-022-12126-3.
Social learning is beneficial for efficient information search in unfamiliar environments ("within-task" learning). In the real world, however, possible search spaces are often so large that decision makers are incapable of covering all options, even if they pool their information collectively. One strategy to handle such overload is developing generalizable knowledge that extends to multiple related environments ("across-task" learning). However, it is unknown whether and how social information may facilitate such across-task learning. Here, we investigated participants' social learning processes across multiple laboratory foraging sessions in spatially correlated reward landscapes that were generated according to a common rule. The results showed that paired participants were able to improve efficiency in information search across sessions more than solo participants. Computational analysis of participants' choice-behaviors revealed that such improvement across sessions was related to better understanding of the common generative rule. Rule understanding was correlated within a pair, suggesting that social interaction is a key to the improvement of across-task learning.
社会学习有利于在不熟悉的环境中进行高效的信息搜索(“任务内”学习)。然而,在现实世界中,可能的搜索空间往往非常大,即使决策者集体汇集信息,也无法涵盖所有选项。处理这种过载的一种策略是开发可推广到多个相关环境的通用知识(“跨任务”学习)。然而,目前尚不清楚社会信息是否以及如何促进这种跨任务学习。在这里,我们在根据共同规则生成的空间相关奖励景观中的多个实验室觅食会议上研究了参与者的社会学习过程。结果表明,配对参与者比单独参与者更能提高信息搜索效率。对参与者选择行为的计算分析表明,这种跨会议的改进与对共同生成规则的更好理解有关。规则理解在一对中是相关的,这表明社会互动是提高跨任务学习的关键。