Theory of mind (ToM) is the ability to understand others’ mental states (e.g., intentions). Studies on human ToM show that the way we understand others’ mental states is very efficient, in the sense that observing only some portion of others’ behaviors can lead to successful performance. Recently, ToM has gained interest in robotics to build robots that can engage in complex social interactions. Although it has been shown that robots can infer others’ internal states, there has been limited focus on the data utilization of ToM mechanisms in robots. Here we show that robots can infer others’ intentions based on limited information by selectively and flexibly using behavioral cues similar to humans. To test such data utilization, we impaired certain parts of an actor robot’s behavioral information given to the observer, and compared the observer’s performance under each impairment condition. We found that although the observer’s performance was not perfect compared to when all information was available, it could infer the actor’s mind to a degree if the goal-relevant information was intact. These results demonstrate that, similar to humans, robots can learn to infer others’ mental states with limited information.

心理理论（ToM）是理解他人心理状态（例如意图）的能力。关于人类行为管理的研究表明，我们理解他人心理状态的方式非常有效，从某种意义上来说，仅观察他人行为的一部分即可取得成功。最近，ToM对机器人技术产生了浓厚的兴趣，以构建可以参与复杂的社交互动的机器人。尽管已经证明机器人可以推断其他人的内部状态，但是对机器人中ToM机制的数据利用的关注仍然有限。在这里，我们展示了机器人可以通过有限和灵活地使用类似于人类的行为提示来基于有限的信息推断他人的意图。为了测试此类数据的利用率，我们削弱了演员机器人向观察者提供的行为信息的某些部分，并比较了观察者在每种损伤条件下的表现。我们发现，尽管与所有可用信息相比，观察者的表现并不完美，但如果与目标相关的信息完好无损，则可以在某种程度上推断演员的思想。这些结果表明，与人类相似，机器人可以学习使用有限的信息来推断他人的心理状态。