In dyadic human-human interactions, individuals may express multiple different facial reactions in response to the same/similar behaviours expressed by their conversational partners depending on their personalised behaviour patterns. As a result, frequently-employed reconstruction loss-based strategies lead the training of previous automatic facial reaction generation (FRG) models to not only suffer from the 'one-to-many mapping' problem, but also fail to comprehensively consider the quality of the generated facial reactions. Besides, none of them considered such personalised behaviour patterns in generating facial reactions. In this paper, we propose the first adversarial FRG model training strategy which jointly learns appropriateness and realism discriminators to provide comprehensive task-specific supervision for training the target facial reaction generators, and reformulates the 'one-to-many (facial reactions) mapping' training problem as a 'one-to-one (distribution) mapping' training task, i.e., the FRG model is trained to output a distribution representing multiple appropriate/plausible facial reaction from each input human behaviour. In addition, our approach also serves as the first offline FRG approach that considers personalised behaviour patterns in generating of target individuals' facial reactions. Experiments show that our PerReactor not only largely outperformed all existing offline solutions for generating more appropriate, diverse and realistic facial reactions, but also is the first approach that can effectively generate personalised appropriate facial reactions. Our code is provided in the supplementary material.

PerReactor: Offline Personalised Multiple Appropriate Facial Reaction Generation

Socially Assistive Robots (SARs) show promise to help children during therapeutic and clinical interventions.
However, using SARs for the evaluation of mental wellbeing of children has not yet been explored. Thus, this paper presents an empirical study with 28 children of 8-13 years old interacting with a Nao robot in a 45-minute session where the robot administered (robotised) the Short Mood and Feelings Questionnaire (SMFQ) and the Revised Child Anxiety and Depression Scale (RCADS). Prior to the experimental session, we also evaluated children’s wellbeing using established standardised approaches via online RCADS questionnaires filled by the children (self-report) and their parents (parent-report). We clustered the
participants into three groups (lower, medium, and higher tertile) based on their SMFQ scores. Further, we analysed the questionnaire responses
across the three clusters and across the different modes of administration (self-report, parent-report, and robotised).
Our results show that the robotised evaluation seems to be the most suitable mode in identifying wellbeing related anomalies in children across the three clusters of participants as compared with the self-report and the
parent-report modes. Further, children with decreasing levels of wellbeing (lower, medium and higher tertiles)
exhibit different response patterns: higher tertile are more negative in their responses with the robot while the lower tertile are more positive in their responses with the robot. Findings from this work show that SARs can be used to proactively evaluate mental wellbeing 
related concerns in children.

Can Robots Help in the Evaluation of Mental Wellbeing in Children? An Empirical Study

In this paper, we conduct a longitudinal user study to investigate the differences in interactions participants had with an experienced human coach (HC) delivering mindfulness training with the interactions another group of participants had with a Robot Coach (RC) teleoperated by the HC. We aim to gain an understanding of the
evolving user perceptions towards the coaches (HC and RC), which can, in turn, help us design effective strategies to develop autonomous robot coaches that can deliver mental wellbeing interventions.

Towards a context-based Bayesian recognition of transitions in locomotion activities

Recent research is emerging in the field of Social Robotics where robots have the potential to serve as tools to improve human well-being. However, research exploring the expectations and perceptions of prospective users of such robots, and the professionals who currently deliver these interventions, is limited. In this paper, we present qualitative analysis of discussions with prospective users and experienced coaches regarding the design of robot well-being coaches. We invited participants interested in well-being practices to take-part in a Participatory Design (PD) study, consisting of individual interviews and a focus group discussion (N_P = 8). Discussions focused on ideating how a robot could function as a mental well-being coach, based on their experiences with well-being practices. Data triangulation was employed by interviewing three professional coaches as additional sources of information. This resulted in a rich set of data, which we transcribed and analysed using Thematic Analysis (TA). The developed themes regarding robot features, form, behaviours, robot-led well-being practices, and the advantages and disadvantages these could provide, were compiled and are discussed in detail. We present this data together with tabulated quotes from the participants and coaches, to pave the way towards designing robot coaches that can provide supportive interventions to improve the mental health and well-being of their users.

When Positive Perception of the Robot Has No Effect On Learning

Poster Session 3

poster

We are pleased to announce the Thirty-Ninth AAAI Conference on Artificial Intelligence (AAAI-25), which will be held in Philadelphia, Pennsylvania at the Pennsylvania Convention Center from February 25 to March 4, 2025.

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-25 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.

### [Invited Speakers](https://aaai.org/conference/aaai/aaai-25/aaai-25-invited-speakers/)

Register [here](https://aaai.org/conference/aaai/aaai-25/registration/)

AAAI 2025

The purpose of the AAAI conference series is to promote research in Artificial Intelligence (AI) and foster scientific exchange between researchers, practitioners, scientists, students, and engineers across the entirety of AI and its affiliated disciplines. AAAI-25 will feature technical paper presentations, special tracks, invited speakers, workshops, tutorials, poster sessions, senior member presentations, competitions, and exhibit programs, and a range of other activities to be announced.



**Session Chairs: Lynne Baillie, Hatice Gunes**

Long Session III: Child-Robot Interaction

technical paper

**31st IEEE International Conference on Robot & Human Interactive Communication**
 This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.
 
 The conference covers a wide range of topics related to Robot and Human Interactive Communication, involving theories, methodologies, technologies, empirical and experimental studies. Papers related to the study of robotic technology, psychology, cognitive science, artificial intelligence, human factors, ethics and policies, interaction-based robot design and other topics related to human-robot interaction are welcome.
 
 **CONFERENCE THEME:**
 Social, asocial, and antisocial robots
 
 Robots are starting to populate our lives: at work, in our homes, hotels, shops. However, not everybody is comfortable with robots finding a place in society. For example, people may be afraid that robots will replace humans in their jobs. This belief is exacerbated by the media that, on one side, raise expectations of robots’ capabilities, while amplifying fears and worries on the other side.
 
 In the next years, due to the increasing request for interaction with people in social environments, academic research and market analyses predict that robots will become more and more “social”. But, at the same time, robots may incur the risk of being perceived as “asocial” as their pervasiveness in everyday environments may become an obstacle to social interaction between humans. Or they may even be rejected as “antisocial” if researchers do not take care to develop robots that behave according to the customs and habits of the communities where they are expected to operate.
 
 To prevent this from happening, robotic researchers can no longer take the luxury of being mere technicians. They must be capable of addressing all the challenges raised by future robot-populated communities in a multidisciplinary way. They need to share their knowledge with the public to make people aware of what robots really are, what expectations we can have from them, the risks we may incur, and the possible mitigation plans.
 
 While being open to any kind of contribution related to Human-Robot Interactive Communication, the RO-MAN 2022 conference will emphasize these aspects of robotic research. How can we create robots capable of being welcomed as our assistants and companions in society while, at the same time, not being perceived as “asocial” or “antisocial?” How can we create robots perceived as facilitators of the natural development of human beings and communities, rather than obstacles?
 
 Contributions from different disciplines, not exclusively related to technological development, will be welcomed as crucial to pave the way to global acceptance of future robots with an informed attitude.
 
 [![](https://assets.underline.io/uploads/markdown_image/1/image/af259abe105b3791c498ae1552d75710.png)](https://drive.google.com/file/d/18w73BZPB_JVOgcrcdZDqYpEupwVt4CnU/view?usp=sharing)

A registration is required to access this event page. If you have not already done so, please use the below link to register for the event. 

[Register Here](http://www.smile.unina.it/ro-man2022/welcome-to-ieee-ro-man-2022/)

Registration Is Required

IEEE RO-MAN 2022

31st IEEE International Conference on Robot & Human Interactive Communication
This conference is a leading forum where state-of-the-art innovative results, the latest developments as well as future perspectives relating to robot and human interactive communication are presented and discussed.


**Session Chairs:** Mead, Ross (Semio) and Tatarian, Karen (SoftBank Robotics and Sorbonne University)

Panel 11 - Applications of Social Robots 2

panel

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. This theme also touches upon people's expectations and perceptions of robots, as well as other social, cognitive and cultural factors that will influence human-robot interactions. We will have a special session/track on this topic, invite targeted submissions and include plenary speakers who are specialist in this area. We sincerely hope that this focus will help enlighten the design-thinking of all of us as we fabricate and program our own various systems.

To access RO-MAN Virtual 2021, [please register here.](https://ro-man2021.org/registration/)

IEEE RO-MAN 2021

RO-MAN 2021's theme is trustworthiness and cooperation. We chose this term well before the pandemic put the world on edge and added a new reason for us to question our own personal safety when in the company of others. But what about in the company of social robots? What would cause us to trust, or not trust, them? How do we as researchers create that feeling, that critical component of any relationship? With social robots, it is of course largely in our power to design the physical form, the control code and the interface software to maximize trustworthiness, facilitate cooperation and enhance the quality of human-robot interaction. 


**Session Chairs:** Yeung, Cynthia (Diligent Robotics) and Weiss, Astrid (TU Wien)

Hatice Gunes

4

Presentations

PerReactor: Offline Personalised Multiple Appropriate Facial Reaction Generation

Can Robots Help in the Evaluation of Mental Wellbeing in Children? An Empirical Study

Towards a context-based Bayesian recognition of transitions in locomotion activities

When Positive Perception of the Robot Has No Effect On Learning

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