Recent studies have revealed the key importance of modelling personality in robots to improve interaction quality by empowering them with social-intelligence capabilities. Most research relies on verbal and non-verbal features related to personality traits that are highly context-dependent. Hence, analysing how humans behave in a given context is crucial to evaluate which of those social cues are effective. For this purpose, we designed an assistive memory game, in which participants were asked to play the game obtaining support from an introvert or extroverted helper, whether from a human or robot. In this context, we aim to (i) explore whether selective verbal and non-verbal social cues related to personality can be modelled in a robot, (ii) evaluate the efficiency of a statistical decision-making algorithm employed by the robot to provide adaptive assistance, and (iii) assess the validity of the similarity attraction principle. Specifically, we conducted two user studies. In the human–human study (N=31), we explored the effects of helper’s personality on participants’ performance and extracted distinctive verbal and non-verbal social cues from the human helper. In the human–robot study (N=24), we modelled the extracted social cues in the robot and evaluated its effectiveness on participants’ performance. Our findings showed that participants were able to distinguish between robots’ personalities, and not between the level of autonomy of the robot (Wizard-of-Oz vs fully autonomous). Finally, we found that participants achieved better performance with a robot helper that had a similar personality to them, or a human helper that had a different personality.

最近的研究表明，在机器人中建立人格模型对于通过赋予社交智能能力来提高交互质量至关重要。大多数研究都依赖与人格特质相关的语言和非语言特征，这些特征与语境高度相关。因此，分析人类在给定背景下的行为方式对于评估哪些社交线索有效是至关重要的。为此，我们设计了一种辅助记忆游戏，要求参与者玩游戏，从内向或外向的助手（无论是人类还是机器人）获得支持。在这种情况下，我们旨在（i）探索是否可以在机器人中模拟与人格相关的选择性言语和非言语社交线索，（ii）评估机器人用于提供自适应协助的统计决策算法的效率，以及（iii）评估相似性吸引原理的有效性。具体来说，我们进行了两次用户研究。在人与人研究（N = 31）中，我们探索了助手的个性对参与者表现的影响，并从该助手中提取了独特的语言和非语言社交线索。在人类机器人研究中（N = 24），我们对机器人中提取的社交线索进行了建模，并评估了其对参与者绩效的有效性。我们的研究结果表明，参与者能够区分机器人的个性，而不是机器人的自主水平（绿野仙踪与完全自主）。最后，