1,720,962 research outputs found
Group Dynamics in Human-Robot Interaction: Influence Patterns and Behavioral Responses
No full textIntegrating social robots into everyday life requires a deep understanding of how these agents integrate into group interactions.
While previous studies primarily focus on dyadic interactions, this thesis explores group dynamics in Human-Robot Interaction, focusing on the influence patterns that robots can exert within human-robot groups.
By analyzing participants' behavioral responses to robotic actions, this work investigates both the positive and negative effects of robot influence, from fostering cooperation to the potential risk of social exclusion.
First, the research examines the influence of social robots on team choices.
Studies with children demonstrate that they rarely rely on the robots' atypical behavior or advice that has been proven to be incorrect. Instead, they tend to follow the lead of proactive group members, highlighting the importance of initiative as a leadership trait.
These findings have implications for the design of robotic tutors that could leverage the presence of proactive players to engage the whole group. Additionally, experiments with adults reveal that, although participants do not easily conform to robot-majority groups, increased response times might indicate hesitation when faced with robotic disagreement, suggesting a form of social influence that could be relevant in safety contexts.
Second, the thesis investigates whether robotic influence can be leveraged to promote cooperative behaviors.
Using an experimental paradigm based on the Public Good Game, the findings suggest that cooperative robot behavior alone is not sufficient to increase human cooperation.
Future research is needed to explore more nuanced strategies, such as the integration of robot's social cues. Understanding these dynamics could have broad applications, such as improving teamwork in educational and work settings.
Finally, the effects of social exclusion in human-robot groups are explored, demonstrating that robots can induce feelings of ostracism similar to human excluders. Notably, the exclusion by a robot is perceived as more threatening than the exclusion from a human.
Additionally, excluded individuals with prior exposure to the robot are more likely to apply social strategies similar to those used in human relations to their interaction with the robot.
These findings highlight the need for the development of inclusive robotic cognitive architectures that recognize social exclusion and foster balanced group interactions.
By advancing our understanding of group interactions with robots, this research contributes to the broader common goal of developing social robots that understand humans and adopt behaviors that enable humans to interact effortlessly with them
Artificial Partners to Understand Joint Action: Representing Others to Develop Effective Coordination
Get PDFIn the last years, artificial partners have been
proposed as tools to study joint action, as they would
allow to address joint behaviors in more controlled experimental conditions. Here we present an artificial partner
architecture which is capable of integrating all the available
information about its human counterpart and to develop
efficient and natural forms of coordination. The model uses
an extended state observer which combines prior information, motor commands and sensory observations to infer
the partner’s ongoing actions (partner model). Over trials, these estimates are gradually incorporated into action
selection. Using a joint planar task in which the partners
are required to perform reaching movements while mechanically coupled, we demonstrate that the artificial partner
develops an internal representation of its human counterpart, whose accuracy depends on the degree of mechanical
coupling and on the reliability of the sensory information.
We also show that human-artificial dyads develop coordination strategies which closely resemble those observed
in human-human dyads and can be interpreted as Nash
equilibria. The proposed approach may provide insights for
the understanding of the mechanisms underlying humanhuman interaction. Further, it may inform the development
of novel neuro-rehabilitative solutions and more efficient
human-machine interfaces
At school with a robot: Italian students’ perception of robotics during an educational program.
No full textSocial robots are expected to become more and more used in the education field. However, in the interaction between children and social robots, how robots are perceived in social contexts is still under investigation. In this exploratory study, we aimed to investigate how children’s expectations and demographical characteristics (N= 53, 9-14 years old) influence their perception of robot NAO during an education training program in schools. MANCOVA analysis conducted over questionnaire data indicates a positive correlation between the acceptance of the robot and the enjoyment of interacting with it. We found evidence that the more students accepted the robot, the more they perceived the group environment positively. Through a Correspondence Analysis, we investigate which are the preferred features of a robot according to the age of participants. The study suggests that a better opinion of robotics is a factor that can improve the learning environment in this specific context. Our exploratory study encourages conducting studies in-the-wild using self-reported measures to understand the implication of Child-Robot Interaction better
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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