Learning Through Imitation: An Experiment

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AI Summary

This study investigates whether observing and imitating others can enhance individual decision quality in repeated social learning environments, even when others’ actions convey no additional payoff-relevant information. Employing experimental economics methods, the authors compare agent performance under two conditions: one where agents rely solely on public data and another where they also observe peers’ choices. The results demonstrate that imitation significantly increases the probability of selecting the optimal action. This effect proves robust across varying group sizes and private information structures, revealing that socially transmitted cues devoid of informational content can nonetheless improve collective learning efficiency.

Abstract

We compare how well agents aggregate information in two repeated social learning environments. In the first setting agents have access to a public data set. In the second they have access to the same data, and also to the past actions of others. Despite the fact that actions contain no additional payoff-relevant information, and despite potential herd behavior, free riding and information overload issues, observing and imitating the actions of others leads agents to take the optimal action more often in the second setting. We also investigate the effect of group size, as well as a setting in which agents observe private data and others' actions.

Problem

• social learning
• imitation
• information aggregation
• herd behavior
• optimal action

Innovation

• social learning
• imitation
• information aggregation
• herd behavior
• experimental economics