相关论文: Influence of perspective taking through robotic vi…
Integrating social robots in our group-based society, beyond the technical challenges, requires considering the social group dynamics. Following the results from preliminary exploratory studies on the influence of social robots on group…
Cooperation between self-interested individuals is a widespread phenomenon in the natural world, but remains elusive in interactions between artificially intelligent agents. Instead, naive reinforcement learning algorithms typically…
Virtual agents are commonly used in physical activity interventions to support behavior change, often taking the role of coaches that deliver encouragement and feedback. While effective for compliance, this role typically lacks relational…
As robots have become increasingly common in human-rich environments, it is critical that they are able to exhibit social cues to be perceived as a cooperative and socially-conformant team member. We investigate the effect of robot gaze…
Recent advancements in robotics have increased the possibilities for integrating robotic systems into human-involved workplaces, highlighting the need to examine and optimize human-robot coordination in collaborative settings. This study…
Gaze is a crucial social cue in any interacting scenario and drives many mechanisms of social cognition (joint and shared attention, predicting human intention, coordination tasks). Gaze direction is an indication of social and emotional…
We propose a decision-theoretic framework in which a robot strategically can shape inferred human's prosocial state during repeated interactions. Modeling the human's prosociality as a latent state that evolves over time, the robot learns…
Can artificial agents learn to assist others in achieving their goals without knowing what those goals are? Generic reinforcement learning agents could be trained to behave altruistically towards others by rewarding them for altruistic…
As anthropomorphic agents (AI and robots) are increasingly used in society, empathy and trust between people and agents are becoming increasingly important. A better understanding of agents by people will help to improve the problems caused…
Social Robots in human environments need to be able to reason about their physical surroundings while interacting with people. Furthermore, human proxemics behaviours around robots can indicate how people perceive the robots and can inform…
We advance the understanding of robotic intervention in high-risk scenarios by examining their potential to distract and impede a school shooter. To evaluate this concept, we conducted a virtual reality study with 150 university…
Humanoid robots can benefit from their similarity to the human shape by learning from humans. When humans teach other humans how to perform actions, they often demonstrate the actions, and the learning human imitates the demonstration to…
As robotic systems become more and more capable of assisting humans in their everyday lives, we must consider the opportunities for these artificial agents to make their human collaborators feel unsafe or to treat them unfairly. Robots can…
Using a dual-task paradigm, we explore how robot actions, performance, and the introduction of a secondary task influence human trust and engagement. In our study, a human supervisor simultaneously engages in a target-tracking task while…
This study investigated whether human trust in a social robot with anthropomorphic physicality is similar to that in an AI agent or in a human in order to clarify how anthropomorphic physicality influences human trust in an agent. We…
Within this work, we explore intention inference for user actions in the context of a handheld robot setup. Handheld robots share the shape and properties of handheld tools while being able to process task information and aid manipulation.…
The social acceptance of AI agents, including intelligent virtual agents and physical robots, is becoming more important for the integration of AI into human society. Although the agents used in human society share various tasks with…
Seamlessly interacting with humans or robots is hard because these agents are non-stationary. They update their policy in response to the ego agent's behavior, and the ego agent must anticipate these changes to co-adapt. Inspired by humans,…
The next step for intelligent dialog agents is to escape their role as silent bystanders and become proactive. Well-defined proactive behavior may improve human-machine cooperation, as the agent takes a more active role during interaction…
Tactile interaction plays an essential role in human-to-human interaction. People gain comfort and support from tactile interactions with others and touch is an important predictor for trust. While touch has been explored as a communicative…