scholarly journals Forms and Frames: Mind, Morality, and Trust in Robots across Prototypical Interactions

2021 ◽  
Vol 2 ◽  
pp. 81-103
Author(s):  
Jaime Banks ◽  
Kevin Koban ◽  
Philippe Chauveau
Keyword(s):  
Higher Order ◽  
Social Robots ◽  
Social Robot ◽  
Human Interaction ◽  
Order Interaction ◽  
Play Interactions ◽  
Attitude Shift ◽  
Formal Properties ◽  
Over Time ◽  
Formal Features

People often engage human-interaction schemas in human-robot interactions, so notions of prototypicality are useful in examining how interactions’ formal features shape perceptions of social robots. We argue for a typology of three higher-order interaction forms (social, task, play) comprising identifiable-but-variable patterns in agents, content, structures, outcomes, context, norms. From that ground, we examined whether participants’ judgments about a social robot (mind, morality, and trust perceptions) differed across prototypical interactions. Findings indicate interaction forms somewhat influence trust but not mind or morality evaluations. However, how participants perceived interactions (independent of form) were more impactful. In particular, perceived task interactions fostered functional trust, while perceived play interactions fostered moral trust and attitude shift over time. Hence, prototypicality in interactions should not consider formal properties alone but must also consider how people perceive interactions according to prototypical frames.

scholarly journals Protocol for a Mediated Long-Term Experiment with a Social Robot

2021 ◽  
Author(s):  
Guy Laban ◽  
Arvid Kappas ◽  
Val Morrison ◽  
Emily S. Cross
Keyword(s):  
Social Robots ◽  
Social Robot ◽  
Human Robot Interaction ◽  
Emotional Engagement ◽  
Emotional States ◽  
Cognitive Architectures ◽  
New Findings ◽  
Long Term Experiment ◽  
Over Time

One major challenge faced by human-robot interaction (HRI) researchers is replicating and extending new findings, to better understand how short, constrained laboratory manipulations might translate to real-world scenarios. Since interactions with social robots are novel and exciting for many people, one particular concern is the extent to which people's behavioural and emotional engagement with robots might develop from initial interactions with a robot, when a robot's novelty is especially salient, and be sustained over time. The aim of this paper is to introduce a research protocol for a mediated long-term online experiment for testing the extent to which social robots’ cognitive architectures can elicit emotionally rich disclosures and expressions from people to identify their needs and emotional states over time. Moreover, this protocol introduces experimental methods for investigating people's perceptions of a social robot in their natural settings during prolonged and regular interactions, and evaluating how novelty effects on human-robot interactions change over time.

Stable Competitive Dynamics Emerge from Multispike Interactions in a Stochastic Model of Spike-Timing-Dependent Plasticity

2006 ◽  
Vol 18 (10) ◽  
pp. 2414-2464 ◽  
Author(s):  
Peter A. Appleby ◽  
Terry Elliott
Keyword(s):  
Synaptic Plasticity ◽  
Stochastic Model ◽  
Higher Order ◽  
Spike Timing ◽  
Competitive Dynamics ◽  
Spike Timing Dependent Plasticity ◽  
Interaction Function ◽  
Dependent Plasticity ◽  
Order Interaction ◽  
Synaptic Dynamics

In earlier work we presented a stochastic model of spike-timing-dependent plasticity (STDP) in which STDP emerges only at the level of temporal or spatial synaptic ensembles. We derived the two-spike interaction function from this model and showed that it exhibits an STDP-like form. Here, we extend this work by examining the general n-spike interaction functions that may be derived from the model. A comparison between the two-spike interaction function and the higher-order interaction functions reveals profound differences. In particular, we show that the two-spike interaction function cannot support stable, competitive synaptic plasticity, such as that seen during neuronal development, without including modifications designed specifically to stabilize its behavior. In contrast, we show that all the higher-order interaction functions exhibit a fixed-point structure consistent with the presence of competitive synaptic dynamics. This difference originates in the unification of our proposed “switch” mechanism for synaptic plasticity, coupling synaptic depression and synaptic potentiation processes together. While three or more spikes are required to probe this coupling, two spikes can never do so. We conclude that this coupling is critical to the presence of competitive dynamics and that multispike interactions are therefore vital to understanding synaptic competition.

scholarly journals Higher-order temporal network effects through triplet evolution

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Qing Yao ◽  
Bingsheng Chen ◽  
Tim S. Evans ◽  
Kim Christensen
Keyword(s):  
Real World ◽  
Link Prediction ◽  
Higher Order ◽  
Prediction Algorithm ◽  
Interaction Patterns ◽  
Temporal Networks ◽  
World Systems ◽  
Order Interaction ◽  
Space And Time ◽  
Pairwise Interactions

AbstractWe study the evolution of networks through ‘triplets’—three-node graphlets. We develop a method to compute a transition matrix to describe the evolution of triplets in temporal networks. To identify the importance of higher-order interactions in the evolution of networks, we compare both artificial and real-world data to a model based on pairwise interactions only. The significant differences between the computed matrix and the calculated matrix from the fitted parameters demonstrate that non-pairwise interactions exist for various real-world systems in space and time, such as our data sets. Furthermore, this also reveals that different patterns of higher-order interaction are involved in different real-world situations. To test our approach, we then use these transition matrices as the basis of a link prediction algorithm. We investigate our algorithm’s performance on four temporal networks, comparing our approach against ten other link prediction methods. Our results show that higher-order interactions in both space and time play a crucial role in the evolution of networks as we find our method, along with two other methods based on non-local interactions, give the best overall performance. The results also confirm the concept that the higher-order interaction patterns, i.e., triplet dynamics, can help us understand and predict the evolution of different real-world systems.

scholarly journals Mitigating Children’s Pain and Anxiety during Blood Draw Using Social Robots

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1211
Author(s):  
Matthijs H. J. Smakman ◽  
Koen Smit ◽  
Lotte Buser ◽  
Tom Monshouwer ◽  
Nigel van Putten ◽  
...  
Keyword(s):  
Healthcare Professionals ◽  
Young Patients ◽  
Hospital Setting ◽  
Social Robots ◽  
Social Robot ◽  
Blood Collection ◽  
Medical Procedure ◽  
Blood Draw ◽  
The Social ◽  
Children's Pain

Young pediatric patients who undergo venipuncture or capillary blood sampling often experience high levels of pain and anxiety. This often results in distressed young patients and their parents, increased treatment times, and a higher workload for healthcare professionals. Social robots are a new and promising tool to mitigate children’s pain and anxiety. This study aims to purposefully design and test a social robot for mitigating stress and anxiety during blood draw of children. We first programmed a social robot based on the requirements expressed by experienced healthcare professionals during focus group sessions. Next, we designed a randomized controlled experiment in which the social robot was applied as a distraction method to measure its capacity to mitigate pain and anxiety in children during blood draw in a children’s hospital setting. Children who interacted with the robot showed significantly lower levels of anxiety before actual blood collection, compared to children who received regular medical treatment. Children in the middle classes of primary school (aged 6–9) seemed especially sensitive to the robot’s ability to mitigate pain and anxiety before blood draw. Children’s parents overall expressed strong positive attitudes toward the use and effectiveness of the social robot for mitigating pain and anxiety. The results of this study demonstrate that social robots can be considered a new and effective tool for lowering children’s anxiety prior to the distressing medical procedure of blood collection.

scholarly journals Longitudinal change in restricted and repetitive behaviors from 8-36 months

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Robin Sifre ◽  
Daniel Berry ◽  
Jason J. Wolff ◽  
Jed T. Elison
Keyword(s):  
Measurement Invariance ◽  
Factor Score ◽  
Developmental Change ◽  
Neurodevelopmental Disorder ◽  
Autism Spectrum ◽  
Higher Order ◽  
Repetitive Behaviors ◽  
Restricted And Repetitive Behaviors ◽  
Repetitive Motor ◽  
Over Time

Abstract Background Restricted and repetitive behaviors (RRBs) are core features of autism spectrum disorder (ASD) and one of the earliest behavioral signs of ASD. However, RRBs are also present in typically developing (TD) infants, toddlers, and preschool-aged children. Past work suggests that examining change in these behaviors over time is essential to distinguish between normative manifestations of these behaviors and behaviors that denote risk for a neurodevelopmental disorder. One challenge in examining changes in these behaviors over time is that most measures of RRBs have not established longitudinal measurement invariance. The aims of this study were to (1) establish measurement invariance in the Repetitive Behavior Scales for Early Childhood (RBS-EC), a parent-report questionnaire of RRBs, and (2) model developmental change in RRBs from 8 to 36 months. Methods We collected RBS-EC responses from parents of TD infants (n = 180) from 8 to 36 months (n = 606 responses, with participants contributing an average of 3-time points). We leverage a novel methodological approach to measurement invariance testing (Bauer, Psychological Models, 22(3), 507–526, 2017), moderated nonlinear factor analysis (MNLFA), to determine whether the RBS-EC was invariant across age and sex. We then generated adjusted factor score estimates for each subscale of the RBS-EC (repetitive motor, self-directed, and higher-order behaviors), and used linear mixed effects models to estimate between- and within-person changes in the RBS-EC over time. Results The RBS-EC showed some non-invariance as a function of age. We were able to adjust for this non-invariance in order to more accurately model changes in the RBS-EC over time. Repetitive motor and self-directed behaviors showed a linear decline from 8 to 36 months, while higher-order behaviors showed a quadratic trajectory such that they began to decline later in development at around 18 months. Using adjusted factor scores as opposed to unadjusted raw mean scores provided a number of benefits, including increased within-person variability and precision. Conclusions The RBS-EC is sensitive enough to measure the presence of RRBs in a TD sample, as well as their decline with age. Using factor score estimates of each subscale adjusted for non-invariance allowed us to more precisely estimate change in these behaviors over time.

scholarly journals The Social Robot in Rehabilitation and Assistance: What is the Future?

Healthcare ◽  
2021 ◽  
Vol 9 (3) ◽  
pp. 244
Author(s):  
Daniele Giansanti
Keyword(s):  
The Elderly ◽  
Social Robots ◽  
Social Robot ◽  
Clinical Use ◽  
Research Development ◽  
Future Directions ◽  
Collaborative Robotics ◽  
Research Perspectives ◽  
The Social ◽  
The Future

This commentary aims to address the field of social robots both in terms of the global situation and research perspectives. It has four polarities. First, it revisits the evolutions in robotics, which, starting from collaborative robotics, has led to the diffusion of social robots. Second, it illustrates the main fields in the employment of social robots in rehabilitation and assistance in the elderly and handicapped and in further emerging sectors. Third, it takes a look at the future directions of the research development both in terms of clinical and technological aspects. Fourth, it discusses the opportunities and limits, starting from the development and clinical use of social robots during the COVID-19 pandemic to the increase of ethical discussion on their use.

Symmetry-conserving higher-order interaction terms in the interacting boson model

1985 ◽  
Vol 32 (3) ◽  
pp. 1049-1056 ◽  
Author(s):  
G. Vanden Berghe ◽  
H. E. De Meyer ◽  
P. Van Isacker
Keyword(s):  
Higher Order ◽  
Interacting Boson Model ◽  
Order Interaction ◽  
Interaction Terms ◽  
Boson Model

scholarly journals Ground states of Bose–Einstein condensates with higher order interaction

2019 ◽  
Vol 386-387 ◽  
pp. 38-48 ◽  
Author(s):  
Weizhu Bao ◽  
Yongyong Cai ◽  
Xinran Ruan
Keyword(s):  
Ground States ◽  
Higher Order ◽  
Order Interaction ◽  
Bose Einstein

scholarly journals The Social Robot and the Digital Physiotherapist: Are We Ready for the Team Play?

Healthcare ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1454
Author(s):  
Rossella Simeoni ◽  
Federico Colonnelli ◽  
Veronica Eutizi ◽  
Matteo Marchetti ◽  
Elena Paolini ◽  
...  
Keyword(s):  
Performance Monitoring ◽  
Digital Health ◽  
Social Robots ◽  
Social Robot ◽  
Work Processes ◽  
Feedback Form ◽  
Electronic Survey ◽  
The Social ◽  
Two Samples ◽  
Periodic Monitoring

Motivation: We are witnessing two phenomena. The first is that the physiotherapist is increasingly becoming a figure that must interact with Digital Health. On the other hand, social robots through research are improving more and more in the aspects of social interaction thanks also to artificial intelligence and becoming useful in rehabilitation processes. It begins to become strategic to investigate the intersections between these two phenomena. Objective: Therefore, we set ourselves the goal of investigating the consensus and opinion of physiotherapists around the introduction of social robots in clinical practice both in rehabilitation and assistance. Procedure: An electronic survey has been developed focused on social robot-based rehabilitation and assistance and has been submitted to subjects focused on physiotherapy sciences to investigate their opinion and their level of consent regarding the use of the social robot in rehabilitation and assistance. Two samples of subjects were recruited: the first group (156 participating subjects, 79 males, 77 females, mean age 24.3 years) was in the training phase, and the second (167 participating subjects, 86 males, 81 females, mean age 42.4 years) group was involved in the work processes. An electronic feedback form was also submitted to investigate the acceptance of the proposed methodology. Results: The survey showed a consistency of the results between the two samples from which interesting considerations emerge. Contrary to stereotypes that report how AI-based devices put jobs at risk, physiotherapists are not afraid of these devices. The subjects involved in the study believe the following: (a) social robots can be reliable co-workers but will remain a complementary device; (b) their role will be of the utmost importance as an operational manager in their use and in performance monitoring; (c) these devices will allow an increase in working capacity and facilitate integration. All those involved in the study believe that the proposed electronic survey has proved to be a useful and effective tool that can be useful as a periodic monitoring tool and useful for scientific societies. Conclusions: The evolution of social robots represents an unstoppable process as does the increase in the aging of the population. Stakeholders must not look with suspicion toward these devices, which can represent an important resource, but rather invest in monitoring and consensus training initiatives.

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