Belonging to a group is a natural need for human beings. Being left out and rejected represents a negative event, which can cause discomfort and stress to the excluded person and other members. Social robots have been shown to have the potential to be optimal tools for studying influence in group interactions, providing valuable insights into how human group dynamics can be modeled, replicated, and leveraged. In this work, we aim to study the effect of being excluded by a social robot in a teenagers-robot interaction. We propose a conversational turn-taking game, inspired by the Cyberball paradigm and rooted in social exclusion mechanisms, to explore how the humanoid robot iCub can affect group dynamics by excluding one of the group members. Preliminary results show that the included player tries to re-engage with the one excluded by the robot. We interpret this dynamic as an included player's tentative to compensate for the exclusion and reestablish a balance, in line with findings in human-human interaction research. Furthermore, the paradigm we developed seems a suitable tool for researching social influence in different Human-Robot Interaction contexts.

Human beings are naturally predisposed to affiliate with others; due to this inclination, social exclusion is perceived as an unsettling experience. The recent advancements in robotics highlight how robots have started to be considered social agents, raising the necessity to investigate social mechanisms behind Human-Robot Interactions. This study explores whether being excluded by a social robot elicits similar negative outcomes as being excluded by a human. Using an experimental design inspired by the Cyberball Paradigm, we conducted a between-subjects experiment with sixty-two participants, where the humanoid robot iCub and a human confederate excluded the participants. According to the condition, one of the two partially re-included them. Our findings indicate that when the robot excluded participants completely, they experienced more threats to their fundamental needs and judged the robot more negatively compared to the condition where the confederate totally excluded them. Additionally, the analysis suggests that previous encounters with iCub influenced participant strategies during the exclusion. Those who had interacted with the robot before were more likely to prefer the robot when excluded by it and the confederate when excluded by them, possibly reflecting a preference for the excluder. Participants with no prior experience tended to favor the robot in both conditions. Behavioral analyses provided additional details on the dynamics of the interaction, revealing that participants increased their physical distance from the interaction table over rounds, accompanied by a decrease in happy expressions and an increase in sad expressions. This study provides meaningful insights into the behavioral dynamics of robotic exclusion and its perception, gaining awareness of the importance of designing social robots that can recognize and mitigate social exclusion when interacting with humans.

Recent developments in large language models and multi-agentic systems present both opportunities and challenges for Human-Robot Interaction (HRI). However, it remains unclear how the interaction paradigms will be reshaped due to the growing complexity and opaqueness. Therefore, to bridge this gap and connect users with multi-agentic systems through embodied robot agents, this workshop aims to explore solutions for design challenges of multi-agentic systems on various types of robots in real-world contexts. Through a complementary mix of focus groups, including design activities and paper presentations, our workshop generates design considerations for real-world applications and outlines pioneering research agendas for multi-agentic systems in HRI.