Imitation is a key component of human social behavior, and is widely used by both children and adults as a way to navigate uncertain or unfamiliar situations. But in an environment populated by multiple heterogeneous agents pursuing different goals or objectives, indiscriminate imitation is unlikely to be an effective strategy -- the imitator must instead determine who is most useful to copy. There are likely many factors that play into these judgements, depending on context and availability of information. Here we investigate the hypothesis that these decisions involve inferences about other agents' reward functions. We suggest that people preferentially imitate the behavior of others they deem to have similar reward functions to their own. We further argue that these inferences can be made on the basis of very sparse or indirect data, by leveraging an inductive bias toward positing the existence of different \textit{groups} or \textit{types} of people with similar reward functions, allowing learners to select imitation targets without direct evidence of alignment.

翻译：模仿是人类社会行为的关键组成部分，儿童和成人都广泛将其作为应对不确定或陌生情境的方式。但在一个由追求不同目标或目的的异质代理人组成的环境中，不加区分地模仿不太可能成为一种有效策略——模仿者必须确定最值得模仿的对象。这些判断可能涉及多种因素，具体取决于背景和信息获取情况。本文研究了这些判断涉及对其他代理人奖励函数推断的假设。我们认为，人们倾向于优先模仿那些他们认定具有与自身相似奖励函数的个体的行为。我们进一步论证，这些推断可以基于非常稀疏或间接的数据进行，通过利用一种归纳偏差（即假定存在具有相似奖励函数的群体或类型的人），使学习者无需直接证据便能选择模仿对象。