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Just follow the suit! Trust in Human-Robot Interactions during Card Game Playing


Abstract and Figures

Robots are currently being developed to enter our lives and interact with us in different tasks. For humans to be able to have a positive experience of interaction with such robots, they need to trust them to some degree. In this paper, we present the development and evaluation of a social robot that was created to play a card game with humans, playing the role of a partner and opponent. This type of activity is especially important, since our target group is elderly people-a population that often suffers from social isolation. Moreover, the card game scenario can lead to the development of interesting trust dynamics during the interaction, in which the human that partners with the robot needs to trust it in order to succeed and win the game. The design of the robot's behavior and game dynamics was inspired in previous user-centered design studies in which elderly people played the same game. Our evaluation results show that the levels of trust differ according to the previous knowledge that players have of their partners. Thus, humans seem to significantly increase their trust level towards a robot they already know, whilst maintaining the same level of trust in a human that they also previously knew. Henceforth, this paper shows that trust is a multifaceted construct that develops differently for humans and robots.
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Just follow the suit!
Trust in Human-Robot Interactions during Card Game Playing
Filipa Correia1, Patr´
ıcia Alves-Oliveira2, Nuno Maia1, Tiago Ribeiro1,
Sofia Petisca1, Francisco S. Melo1and Ana Paiva1
Abstract Robots are currently being developed to enter our
lives and interact with us in different tasks. For humans to
be able to have a positive experience of interaction with such
robots, they need to trust them to some degree. In this paper,
we present the development and evaluation of a social robot
that was created to play a card game with humans, playing
the role of a partner and opponent. This type of activity is
especially important, since our target group is elderly people - a
population that often suffers from social isolation. Moreover, the
card game scenario can lead to the development of interesting
trust dynamics during the interaction, in which the human that
partners with the robot needs to trust it in order to succeed
and win the game. The design of the robot’s behavior and game
dynamics was inspired in previous user-centered design studies
in which elderly people played the same game. Our evaluation
results show that the levels of trust differ according to the
previous knowledge that players have of their partners. Thus,
humans seem to significantly increase their trust level towards
a robot they already know, whilst maintaining the same level of
trust in a human that they also previously knew. Henceforth,
this paper shows that trust is a multifaceted construct that
develops differently for humans and robots.
According to the World Population Prospects (http:
//, the United Nations envi-
sions that the world population will dramatically age in
the next few years. As such, the society needs to embrace
this transition and develop ways to deal with it. Moreover,
the elderly population commonly has physical or cognitive
impairments, and current technology offers a possibility to
deal and contribute to the Quality of Life (QoL), leading
to successful aging[1]. In particular, assistive robots play a
significant role in the technological evolution, as they could
eventually be capable of providing elderly care.
However, QoL goes beyond meeting health care needs to
address enjoyable and quality time, ultimately related with
satisfaction towards ones life[2]. Therefore, when dealing
with aged people with no serious health problems, that are
still capable of doing their regular daily tasks, there is still a
need to invest in their QoL, providing ways to occupy their
free time with entertaining activities.
Our previous research [3] has explored the activities in
which independent-living older adults require a robot. A
panoply of different activities that they can still do by their
1Filipa Correira, Nuno Maia, Tiago Ribeiro, Sofia Petisca,
Francisco S. Melo and Ana Paiva is with INESC-ID and
Instituto Superior T´
ecnico, Universidade de Lisboa, Portugal
ıcia Alves-Oliveira is with INESC-ID and Instituto Universit´
ario de
Lisboa (ISCTE-IUL), CIS-IUL, Lisboa, Portugal
own, but with some degree of difficulty, translates their
need for assistance. Moreover, elderly people recurrently
expressed problems related to social isolation and a need to
reconnect. To meet this requirement, this paper presents the
development and evaluation of a robotic game partner and
opponent in a classical card game, which most elders enjoy
playing. The main aim of this research was to develop an
entertaining activity targeting the elderly population, using a
social robot to help reconnecting people.
The card game scenario is an entertainment scenario in
which three people play the game with a robot. This scenario
is part of the PArCEIRO project1, whose purpose is to
study the role of social robotic players during tabletop card
games with humans. The chosen card game was Sueca2,
since it is composed of two teams that simultaneously allow
a partnership between two human players and between a
human and a robotic player. This means our robotic game
player can sustain two roles during the game: partner and
opponent. This game in particular is one of the most played
games among the elderly population in Portugal.
The Artificial Intelligence (AI) for some complex games
has become very strong over the years. In fact, it has already
defeated human world champions, e.g. Deep Blue, Chinook
and Watson [4], [5], [6]. However, the increasing competence
of these artificial players, may lead humans to generally
consider them as fierce competitors. Yet, when we consider
games played in social environments or when they require
the AI to play as a social partner, people may still be wary
of trusting AI to be up to human standards.
To analyze the performance of this scenario and how joyful
participants felt, we conducted two user studies: one in a
controlled lab environment, and another into-the-wild. We
were interested in measuring the trust levels that participants
felt towards the robot as a partner, and compared them to the
trust felt towards human partners. Moreover, we analyzed the
positive and negative affect after the study, and compared it
with their baseline level. Finally, we studied the usability of
our system and how expert Sueca players feel when they
interact with it.
A. Elderly and Robots
Several projects have been investing in robotic technology
to enhance QoL and successful aging, such as the ACCOM-
2 (card game)
25th IEEE International Symposium on
Robot and Human Interactive Communication (RO-MAN)
August 26-31, 2016. Columbia University, NY, USA
978-1-5090-3928-9/16/$31.00 ©2016 IEEE 507
PANY project3, CARE4, ENRICHME5, ExCITE6, Giraff-
Plus7, HOBBIT8, RAMCIP9, Robot-Era10 and SILVER11.
Moreover, Broekens et al. (2009), have reviewed robotic
technologies in elderly care and have emphasized the positive
effects of social assistive robots [7]. These kind of robots
may vary from a service type to a companion type. The
first ones are essentially focused on enhancing QoL aging of
independently living elders. On the other hand, companion
robots are also being used with therapeutic purposes.
In the service type, robots such as Pearl[8], Care-O-
bot II[9], RoboCare[10] present many similarities regarding
the guidance through environments and the management of
elders’ everyday activities. Their differences reside in their
sensors and the interface of communication with the users.
Overall, these robots were developed to provide home assis-
tance for elders with an independent living or to complement
caregivers’ support.
In the companion type, the Paro robot was used in a one-
year study with elderly participants possessing different lev-
els of dementia and revealing increases on their moods and
depression levels. Another example is the Huggable robot
that was developed to accompany patients in hospitals. Both
robots present extremely reactive functionalities regarding
touch and voice inputs, and their primary goal is therapeutic.
Indeed, technology seems to be perceived as helpful for
the elderly population, both for assistive purposes as well as
for entertaining activities.
B. Entertainment Robots
Game playing scenarios are rich environments to develop
human-robot interactions and the usage of social and emo-
tional robots has been regarded as more entertaining and
enjoyable when compared to virtual characters [11]. Leite
et al. (2009), developed a robotic chess tutor for children
and have analyzed how its social and empathic behaviors
can improve children’s engagement during the game [12].
Another social robotic game player is EMotive heaY systeM
(EMYS) the Risk player that was used to improve social
presence of an artificial opponent in the board game [13].
The role of robots in entertaining activities seems to have
its importance, and more work needs to be developed to
increase the usage of robots as a tool that re-connect people
and provide joyful moments. In this paper, we developed
an entertaining scenario in which elderly people and robots
meet to play a classic card game.
C. Trust in Human-robot and Human-Human Relationships
According to Hanook et al. (2011), a human must trust a
robot when interacting with it to have an effective usage of
its capabilities, and to accomplish a common goal between
them, in the case of a human-robot team. The authors
conducted several experiments to examine which factors
influence the trust measure in this type of relationship, and
their studies revealed that trust in human-robot interaction is
a constellation of three factors: human-related; robot-related
and environmental. However, human-related factors (e.g.
attentional capacity and personality traits) and environmental
(e.g. task type and culture) presented a moderate effect
on trust, whilst robot-based factors, especially performance-
based, influenced the most trust towards a robot [14].
Thus, trust appears as a complex construct, especially
linked to the robot’s performance. However, trust in human-
human relationships appears also as a complex construct with
variables related to those of human-robot trust. Indeed, the
actions of the other seem to contribute to the trust we deposit
in one another. This is then related with the performance of
the other, e.g., the type of decisions he/she performs, etc.
Moreover, trust in human-human relationships is connected
with the recognition of positive expectations for the other,
despite of the inherent uncertainty. This includes cognitive,
behavioral and affective states that we expect the other to
have according to a given situation [15].
In this paper we have considered trust as a construct that
informs us about the quality of the human-robot interaction
in comparison with human-human interaction.
The goal of the aforementioned scenario was to create an
autonomous robot that is able to play the Sueca card game
on a touch table, and socially interact with its partner and
its two opponents in context of the game. To achieve this
goal, the design involved two different concerns: how can
the social robot behave in a human fashion during the game
(Section III-A); and how can the game interface handle the
interaction between humans and a robot while respecting the
usual game dynamics of Sueca (Section III-B).
A. Behavior Design for our Social Robot
According to Braezeal (2003), the robot’s sociability in-
creases with the ability to support a social model adapted
to the environment [16]. As a result, we conducted a user-
centered study to understand how human players behave
during Sueca games, and to further include those behaviors
in the design of our social robot.
The user-centered study took place in an Elder Care
Center, where participants were told to play Sueca for as long
as they wanted. The four male participants played 10 games
during about 30 minutes and their performances were audio-
and video-recorded for further behavioral analysis. Figure 1
illustrates participants setup during the user-centered study.
The behavioral analysis of the videos allowed us to obtain
a list of game events that contains specific moments during
a game where participants changed their previous behavior
or interacted with other players. Moreover, we collected
their verbal and non-verbal behaviors for each corresponding
game event. We have also observed that the same game event
Fig. 1: Elders playing Sueca during the user-centered study.
produces different behaviors according to who is doing it,
i.e. self, a partner or an opponent. For instance, participants
frequently used an encouraging tone when talking to their
partners and a competitive tone to their opponents. The final
list of our social robot’s utterances was inspired by all the
collected behaviors from the user-centered study and some
examples can be seen in Table I. Additionally, the video12
presented in [17] illustrates the social performance of our
robotic game player, which was implemented on an EMYS
TABLE I: Examples of utterances of the social robotic player.
Game Event Utterance
own cards
<gaze(ownCards)>Let’s see...
the trick
<gaze(opponent1)>Although I don’t know where
the ace is, <glance(opponent2)>I will cut
<glance(playingCard)>this one!
An opponent
cuts the trick
<gaze(partner)>What a bad luck... Look partner,
<glance(table)>he cut it! <glance(opponent)>
B. Entertainment Activity
In the previously mentioned user-centered study, we could
also analyze the game flow of human players playing Sueca
in the traditional scenario, and create the main usability
requirements for the game interface of our scenario.
Sueca is a popular and traditional Portuguese card game
among several age groups, including the elderly. Hence,
its players are accustomed to a very specific game flow
and speed, as well as the touch and feel of holding the
cards. Furthermore, since it is a team game, some partners
might even reach an intimacy level where they imperceptibly
cheat through gestures, looks or moves, which confirms the
engaging game experience some players are used to.
We have noticed participants attached great importance to
their cards during the game. Firstly, they had to hold them
in a way nobody else could see them. Secondly, their hands
were at the locations they have most frequently looked at,
which we attributed as a sign of deliberation about their
next moves. As a result, our system had to use physical
cards at the same time as it provides a mechanism for the
robot to play and recognize the others plays. This usability
requirement might be granted using a multimodal interface
over a touch table that is capable of recognizing the cards,
e.g. using fiducial markers on cards.
Considering this approach, we also analyzed the location
that participants typically throw their cards over the table.
The relevance of this question consisted in creating a mech-
anism to solve the possible overlap between cards. However,
we have noticed that participants usually place their cards
in the center of the table, although as near as possible to
their location, so that other players can understand who has
played each card. Additionally, if, after throwing a card, it
overlapped another, participants have always adjusted the
cards position, which eliminates the overlapping problem.
In order to simplify the development and integration of
our robot with the game, we use the SERA ecosystem[18],
as shown in Figure 2. The Thalamus system provides the
integration framework of all modules, Skene is the semi-
autonomous behavior planner that uses a high-level language
to manage the robot’s behaviors, and Nutty Tracks is the
robot’s animation engine.
Fig. 2: The architecture of the Sueca-playing robot.
The Decision Maker Module represents our robotic agent
in this system, and is divided into two modules, one for
each of its main tasks, i.e. to compute the game and to
prescribe social behaviors. Nonetheless, these two modules
are regularly communicating with each other in a symbiotic
manner to combine their outputs in a proper way. An example
that illustrates this cooperational concept between the two
modules is an opponent playing a card, which may trigger
a behavior associated to the game event opponent play. At
the same time, that play is computed in the current game
state of the agent to calculate the benefit it produces for its
team and that value can even be mentioned by the robot in
a sentence and be used to update its emotional state. This
emotional state is used in the Decision Maker Module and is
produced by FAtiMA, the emotional agent architecture[19],
in order to update the robots behaviors and posture.
When the AI Module has to choose a card to play, it uses
the Perfect Information Monte-Carlo (PIMC) algorithm in its
deliberation process. This algorithmic approach has obtained
remarkable results in similar AIs for hidden information
trick-taking card games, e.g. Bridge[20] and Skat[21].
The Sueca Game Module provides the interface, game
engine and is also responsible for the physical cards recog-
nition. Our deck had to be redesigned so that each card
can include fiducial markers and, therefore, can be detected
by the touch table13 using the recTIVision framework14,
see Figure 3. The robots physical cards are recognized at
the beginning and then virtually played during the game.
In this recognition phase, the cards are placed facedown,
which justifies the need to include forwards a fiducial marker.
Figure 4(a) illustrates the usage of the cards either by the
robot and the human players.
Fig. 3: Standard french deck card, on the left, and our
redesigned card with a fiducial marker, on the right.
Nonetheless, the usage of physical cards also brought
some limitations. Firstly, the differences between our version
of cards and the traditional ones were pointed out as confus-
ing and some players have sometimes played incorrectly due
this misunderstanding. The purpose of the black background
is to contrast with the white maker contour, and the more
isolated the marker is, the better it will be recognized. The
second limitation is the markers’ recognition, which failed
in 4 out of 100 games.
Two different studies were performed with the Sueca
scenario: a lab study (see Section V-A) to analyze the trust
levels of participants when partnering with a robot or a
human during the card game; and an into-the-wild study (see
Section V-B) in which we deployed our scenario in a Sueca
tournament, providing an opportunity to test the game-play
of this scenario with users that are expert Sueca players.
A. Lab study
This study was run in a lab and participants were adults
who volunteered for the experiment. Although the target
group for this scenario is elderly people, it is required to
test the system before to understand how it is performing
in a controlled lab setting. To do this, we conducted a lab
study with the goal being to test if the scenario is stable
enough. As Sueca is a partnership game, the aim goal of
this study was to analyze the trust levels that humans feel
towards their human or robotic game partners. As robots are
a type of technology that usually triggers a novelty effect,
we thus target the study of trust levels according to previous
knowledge that participants had on their game partners
(either humans and robot). This was possible, as some of the
recruited participants participated in previous studies with
the EMYS robot, and thus, had already interacted with it.
In a similar way for the human-human partnership, some
participants knew each other before playing the game, while
others were strangers.
1) Procedures and Methodology: Each session involved
three participants playing Sueca with the EMYS robot and
lasted about one hour. At the beginning, participants’ part-
ners were selected in a draw so that one of them would
be the robot’s partner and the other two would be each
other’s partner. Before the game-play, they answered to a
questionnaire to assess their affect (PANAS Questionnaire
[22]), and the Human-Robot Trust Questionnaire [23] with
an adapted version for participants with a human partners.
The Human-Robot Trust Questionnaire measures trust in a
scale ranging from 0% of trust to 100% of trust. We aimed
to measure participants emotional state before the game, and
also their trust expectation towards their partners. To have
a standardized version of the game during the study one
researcher explained the game rules and played Sueca with
the three participants using the traditional french deck, before
they started to play with the robot. Afterwards, participants
were invited to play the game with the EMYS robot in a mul-
titouch table, where the three participants played a session
of five games with the robot (see Figure 4(a)). At the end of
the five games, they answered to the post-questionnaires of
PANAS, the Human-Robot Trust Questionnaire, and to some
demographic questions. The goal was to compare the trust
levels of participants towards the robot or the human partner
according to their previous knowledge of the same partners,
i.e., if it was a first interaction with them or if they already
had interacted with each other.
2) Sample: This study included 60 participants (M=24.31,
SD=3.852; 20 females, 39 males, 1 unknown). 20 participants
had EMYS as their game partner, while 40 had a human
partner during the experiment. The majority of participants
classified themselves with a medium level of proficiency
in the Sueca game. We measured the robot’s performance
during the game to assure that the robot’s ability to play did
not interfere with the trust levels that participants felt towards
it. Henceforth, its performance was measured according to
the percentage of won and drawn sessions by its team. They
won 12 sessions out 20 (60%) and drew 1 session (5%). This
led us to conclude that the robot performed well during the
game and showed a good playing ability.
3) Trust Level in the Game Partner: The trust levels
were analyzed according to two factors: the partner type
(human vs. robot); and the partner knowledge, i.e., the
level of previous interaction with the assigned partner (in
the demographics questionnaire this was controlled using
the following statements: “I have never seen my partner
before” vs. “I have already interacted with my partner”.
We used a Mixed ANOVA statistical test to analyse if the
aforementioned factors influenced the trust levels felt by
the participants towards their partner. Results presented a
significant difference between the trust levels before and after
playing the game according to each possible partner type and
partner knowledge (F(1;49)=7.093, sig=.010). Thus, when
analyzing the participants that had no previous interaction
with their partners before the game, we can see that those
who partnered with a human seem to increase their levels of
trust on their partner (74.50% to 81.47%) when compared
to participants who partnered with the robot (66.38% to
65.64%) (see Figure 5. (a)). When analyzing the results for
the participants that had already interacted with their game
partner before, we can see the emergence of a different
pattern. In fact, participants who partnered with a human
(a) (b)
Fig. 4: Participants playing the Sueca card game with the EMYS robot during (a) the lab study and (b) the Sueca tournament.
that they had already interacted with, showed equivalent level
of trust on their partner (79.86% to 81.14%) (see Figure 5.
(b)). Conversely, participants who had EMYS as their partner
in the game and that had already interacted with it, show
an increase on their trust level (from 61.39% to 70.37%).
Moreover, the level of trust in human partners always appears
to be higher than of the trust level in the robot.
(a) (b)
Fig. 5: Trust towards a human partner and a robotic partner
according to the previous level of interaction with the partner,
none in (a) and high in (b).
4) Affect: The PANAS Questionnaire specifies the emo-
tional state into two dimensions: the positive affect and
negative affect scales. We run a Mixed ANOVA statistical test
on data and the results showed that the positive affect signifi-
cantly increased when compared the affect before (M=29.77;
SD=6.84; M=31.35; SD=8.11, for human and robot partners)
and after (M=32.80; SD=7.75; M=33.15; SD=9.16, for hu-
man and robot partners) playing the game, F(1;58)=7.564,
sig=.008, with no significant difference between conditions,
F(1;58)=.488, sig=.488. These results shows that indepen-
dently of having a robotic or a human partner in the game,
participants felt with higher positive affect values after the
interaction, revealing that the entertaining scenario triggers
positive affect states in the players. When looking at the
negative affect, results do not present significant differences
before (M=11.48; SD=2.18; M=13.35; SD=4.25, for human
and robot partners) and after playing the game (M=12.58;
SD=2.98; M=13.25; SD=4.15, for human and robot partners),
F(1;58)=1.257, sig=.267. Moreover, there was no significant
difference for the negative affect before and after playing
the game between different partner types F(1;58)=1.810,
sig=.184. This shows that the negative affect did not increase
after playing the game with the robot.
B. Into-the-wild study
This study was conducted during a Sueca tournament,
where we aimed to examine different users interacting with
the system, possibly including proficient Sueca players. For
this experiment, the set-up was placed in a formal Sueca
Tornament that occurs every year in a Lisbon area (see
Figure 5. (b)).
1) Sample: The session lasted about 2 hours and the 15
subjects played 13 games with EMYS. Each group of three
participants had played between one or three consecutive
games. Then, participants and some members of the audience
were asked to answer a questionnaire about their opinions
related to the robot and the game experience using the
multitouch table to play a classical card game. Thus, 15
participants and 2 members of the audience answered the
questionnaire (M=22.62 years old, SD=10.73; 2 female, 14
male, 1 unknown).
2) Results: EMYS performance was evaluated using three
multiple-choice questions:
Question 1: “How well did EMYS play?”
Question 2: “Which kind of mistakes did it commit?”
Question 3: “Does EMYS play like a human player?”
Results show that EMYS’ plays were mainly classified as
“It always played well” (70,6%), and participants reinforced
this idea in the second question by mainly answering “It
always played well” (75%). In the third question, the mode
of the answers was “It is similar to a human player, although
with some differences” (80%). Secondly, we tried to evaluate
their perception of the game in terms of usability, considering
it was a new experience playing a card game with phys-
ical cards over a multitouch table. The questionnaire also
included two questions related with game dynamics using
this type of technology:
Question 4: “Did you like to play/watch the game over
the touch table?”
Question 5: “Which problems do think are relevant
about this experience over the touch table?”
The majority of the participants answered that they “loved
the experience” (64,7%). For question 5, although 25% found
that “There were no problems”, the remaining answers were
spread between “Sometimes the table takes too long to
recognize the cards” (30%) and “The game flow is not
natural” (35%). Interestingly, the Sueca champions did not
want to play with EMYS. As this was a curious behavior,
we talked to a few of them, and they answered they are “not
willing to lose their reputation by losing with a robot..
In this paper we presented the development and evaluation
of an entertainment scenario with a robot. The underlying
motivation of this work was to meet (some of the) needs
of the elderly population related with social isolation. This
paper shows the design process of the scenario and the
robot’s behavior, as well as its evaluation in a controlled lab
study and in a real-world context. As this scenario is about
a card game in which people need to team up with their
partners to beat their opponents, we measured the level of
trust felt by participants towards their human/robot partner.
We conclude that humans do trust a robot as a partner, but
the trust level varies according to their previous knowledge
of interaction with the same robot. Thus, participants that
had already interacted with the EMYS robot, increased
their level of trust after the game more than participants
that had already interacted with human partners. However,
participants without previous knowledge of their robotic
partner did not increase their trust levels, suggesting that
the development of trust towards robots may need longer
interactions. These findings assist previous theories of trust,
in which this concept appears as a complex construct.
Indeed, trust in robots appears to be directly associated with
performance, and since the robot had a good performance
in terms of playing the game, humans trust it to be their
partners. As for humans, trust between them seems to be
linked not only with performance but also with expectations
towards their behaviors, cognition and emotions, increasing
the complexity of this concept. In line with this, trust between
humans involves more than playing a game with them.
This scenario was also tested in the real world with the
into-the-wild study, which suggested a successful perfor-
mance of the social robotic autonomous partner in the Sueca
card game for an uncontrolled environment.
Overall this study shows the success of implementing a
social robot as a partner in a card game scenario, which is
technically stable and reliable to be further tested with the
elderly people. Therefore, our future work is to understand
the impact this can have in their QoL.
This work was supported by national funds through
ao para a Ciˆ
encia e a Tecnologia (FCT) with refer-
ence UID/CEC/50021/2013. P. Alves-Oliveira acknowledges
a FCT grant ref. SFRH/BD/110223/2015 and T. Ribeiro
FCT grant ref. SFRH/BD/97150/2013. The authors are solely
responsible for the content of this publication. It does not
represent the opinion of the EC, and the EC is not responsible
for any use that might be made of data appearing therein. The
authors show their gratitude to Centro de Dia da Santa Casa
da Miseri´
ordia de Lisboa and to Par´
oquia de Santa Teresinha
for their involvement in the studies.
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... The results suggest an inverse proportional relationship between cognitive load, measured by the change of pupil size of the participants and trust. Correia et al. [9] designed a card-playing game in which human card players were partnered with robots and humans. In this study, the authors focused on showing whether the level of trust can be developed differently for humans and robots. ...
... We note that our proposal is also well aligned with the studies that aim at determining the trust factor of humans in artificial agents. For instance, the studies that we introduce in Section II also emphasize that cognitive load and emotion are two potent elements for humans to establish trust in artificial and biological agents [6], [7], [8], [9]. ...
... Other research has shown similar context effects during studies of robots engaged in physical game playing [20,21], as well as effects from robot group size [22]. The contextual factors in those cases included not only the physical embodied form of the robots, but also their behaviors and ability to elicit trust/empathy from human interactors in order to accomplish shared goals. ...
... Indeed, the component capabilities are deeply interlinked to the characters' cooperative actions and game session evolvement-a known pre-requisite for creating a successful interactive conversational agent [57]. This situatedness demands an empirical (in our case data-driven) design approach, which aligns with best practices for designing immersive voice interaction [21]. It also highlights how that same process can be used to create customizable social environments to explore a broad range of hypotheses related to how contextual factors relate to people's perceptions of interactive technology. ...
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The development of new approaches for creating more “life-like” artificial intelligence (AI) capable of natural social interaction is of interest to a number of scientific fields, from virtual reality to human–robot interaction to natural language speech systems. Yet how such “Social AI” agents might be manifested remains an open question. Previous research has shown that both behavioral factors related to the artificial agent itself as well as contextual factors beyond the agent (i.e., interaction context) play a critical role in how people perceive interactions with interactive technology. As such, there is a need for customizable agents and customizable environments that allow us to explore both sides in a simultaneous manner. To that end, we describe here the development of a cooperative game environment and Social AI using a data-driven approach, which allows us to simultaneously manipulate different components of the social interaction (both behavioral and contextual). We conducted multiple human–human and human–AI interaction experiments to better understand the components necessary for creation of a Social AI virtual avatar capable of autonomously speaking and interacting with humans in multiple languages during cooperative gameplay (in this case, a social survival video game) in context-relevant ways.
... Часть исследований ориентировано на применение моделирования эмоций для генерации человекоподобных реакций, что обогащает взаимодействие человека и искусственного агента [11,44]. Примерами таких проектов с искусственными эмоциональными агентами являются роботы-сиделки для ухода за пожилыми людьми [14] и приложения, которые помогают принимать сложные решения [25]. Целью теоретических исследований обычно выступает моделирование механизмов естественных эмоций для проверки гипотез о человеческом эмоциональном аппарате [29]. ...
... Архитектура. Многие когнитивные архитектуры, как и другие проектируемые системы, являются модульными [14,15]. Это связано прежде всего с тем фактом, что модульность относится к основным принципам инженерии. ...
... For example, some authors have shown that the elder may find the robot useful, but only for certain tasks [25] . Other present-day studies have attempted to assess the effect of a robot-committed error in trust, but they have considered contexts of mild severity of robot error, such as in card games [26] , Lego games [27] , robotic suitcase [28] or other simple domestic tasks (navigating the house, setting a table, playing music) [29] . Hence, it is imperative to consider highsensitivity tasks (e.g., health-related), for which the robot's success rate might have considerable implications on trust. ...
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The efforts to promote ageing-in-place of healthy older adults via cybernetic support are fundamental to avoid possible consequences associated with relocation to facilities, including the loss of social ties and autonomy, and feelings of loneliness. This requires an understanding of key factors that affect the involvement of robots in eldercare and the elderly willingness to embrace the robots’ domestic use. Trust is argued to be the main foundation of an effective adult-care provider, which might be more significant if such providers are robots. Establishing, and maintaining trust usually involves two main dimensions: 1) the robot’s reliability (i.e., performance) and 2) the robot’s intrinsic attributes, including its degree of anthropomorphism and benevolence. We conducted a pilot study using a mixed methods approach to explore the extent to which these dimensions and their interaction influenced elderly trust in a humanoid social robot. Using two independent variables, type of attitude (warm, cold) and type of conduct (error, no-error), we aimed to investigate if the older adult participants would trust a purposefully faulty robot when the robot exerted a warm behaviour enhanced with non-functional touch more than a robot that did not, and in what way the robot error affected trust. Lastly, we also investigated the relationship between trust and a proxy variable of actual use of robots (i.e., intention to use robots at home ). Given the volatile and context-dependent nature of trust, our close-to real-world scenario of elder-robot interaction involved the administration of health supplements, in which the severity of robot error might have a greater implication on the perceived trust.
... For example, there are works which aim to design models for robots to appropriately approach a human to initiate a conversation [3,4] and to maintain appropriate distance with a human during interaction [5]. With a recent shift of focus towards group interaction, however, new application areas have emerged, such as surveillance [6][7][8], playing games with groups of people [9,10], studying human behaviour in a group interaction [2,11], and tracking groups [12][13][14][15]; while relevant for understanding group dynamics, there still remains a gap in the research on how to ensure that robots are able to join an ongoing group interaction. Most of the works mentioned here do not use a robot in their experiments and some works which do use a robot consider the robot to be a part of the group. ...
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The ability of a robot to detect and join groups of people is of increasing importance in social contexts, and for the collaboration between teams of humans and robots. In this paper, we propose a framework, autonomous group interactions for robots (AGIR), that endows a robot with the ability to detect such groups while following the principles of F-formations. Using on-board sensors, this method accounts for a wide spectrum of different robot systems, ranging from autonomous service robots to telepresence robots. The presented framework detects individuals, estimates their position and orientation, detects groups, determines their F-formations, and is able to suggest a position for the robot to enter the social group. For evaluation, two simulation scenes were developed based on the standard real-world datasets. The 1st scene is built with 20 virtual agents (VAs) interacting in 7 different groups of varying sizes and 3 different formations. The 2nd scene is built with 36 VAs, positioned in 13 different groups of varying sizes and 6 different formations. A model of a Pepper robot is used in both simulated scenes in randomly generated different positions. The ability for the robot to estimate orientation, detect groups, and estimate F-formations at various locations is used to determine the validation of the approaches. The obtained results show a high accuracy within each of the simulated scenarios and demonstrates that the framework is able to work from an egocentric view with a robot in real time.
Conference Paper
Human-machine communication has evolved from one-to-one to multi-agent systems where the interplay between machines themselves interacts with human perception and behavior, complicated by unconstrained emotion-based variables in social systems. To investigate Human-Robot and Robot-Robot-Human interaction while constraining the interaction variables in a rule-based system, we developed an artistic intervention using competitive game performance between robotic arms. Two robots play chess with each other while expressively making gestures like thinking, examining, hesitating, shows of satisfaction and bewilderment, breathing, etc. These nonverbal behaviors and evolving rules between games tell a narrative of power struggle between two robots of aggressive vs. reflective personalities. We used recorded videos to assay audience interpretations of individual and robot-to-robot expressions, finding that gestures like standing and confirming were perceived as aggressive, while head turns, deliberation, and audience alerts were seen as curious. Human perception of robot play-style and their own intended play strategies were influenced by robot-robot interactions, such as holding defensive strategies when the robot was deemed aggressive. Robotic movements caused audiences to attribute personality characteristics to them, modifying their intended strategy in patterns like pretending to be friendly first to lull the robot opponent. Our work uses artistic metaphors to study multi-agent environments that cannot be easily controlled for in scientific settings.
In naher Zukunft sind Roboter im Alltag nicht mehr wegzudenken. Sie werden in den unterschiedlichsten Lebensbereichen vorzufinden sein – als täglicher Freund und Helfer in den eigenen vier Wänden, als Assistent in Läden, Einkaufszentren und Hotels oder als Therapeut im Bereich Rehabilitation und Mobilität. Aktuelle Entwicklungen und Trends in diesen Bereichen werden vorgestellt. Außerdem gibt der Beitrag einen Überblick über die verwendeten Technologien und geht auf technische Anforderungen und Herausforderungen in der Robotik ein.
Background: Advancements in science and various technologies have resulted in people having access to better health care, a good quality of life, and better economic situations, enabling humans to live longer than ever before. Research shows that the problems of loneliness and social isolation are common among older adults, affecting psychological and physical health. Information and communication technology (ICT) plays an important role in alleviating social isolation and loneliness. Objective: The aim of this review is to explore ICT solutions for reducing social isolation or loneliness among older adults, the purpose of ICT solutions, and the evaluation focus of these solutions. This study particularly focuses on customized ICT solutions that either are designed from scratch or are modifications of existing off-the-shelf products that cater to the needs of older adults. Methods: A scoping literature review was conducted. A search across 7 databases, including ScienceDirect, Association for Computing Machinery, PubMed, IEEE Xplore, PsycINFO, Scopus, and Web of Science, was performed, targeting ICT solutions for reducing and managing social isolation and loneliness among older adults. Articles published in English from 2010 to 2020 were extracted and analyzed. Results: From the review of 39 articles, we identified 5 different purposes of customized ICT solutions focusing on reducing social isolation and loneliness. These were social communication, social participation, a sense of belonging, companionship, and feelings of being seen. The mapping of purposes of ICT solutions with problems found among older adults indicates that increasing social communication and social participation can help reduce social isolation problems, whereas fulfilling emotional relationships and feeling valued can reduce feelings of loneliness. In terms of customized ICT solution types, we found the following seven different categories: social network, messaging services, video chat, virtual spaces or classrooms with messaging capabilities, robotics, games, and content creation and management. Most of the included studies (30/39, 77%) evaluated the usability and acceptance aspects, and few studies (11/39, 28%) focused on loneliness or social isolation outcomes. Conclusions: This review highlights the importance of discussing and managing social isolation and loneliness as different but related concepts and emphasizes the need for future research to use suitable outcome measures for evaluating ICT solutions based on the problem. Even though a wide range of customized ICT solutions have been developed, future studies need to explore the recent emerging technologies, such as the Internet of Things and augmented or virtual reality, to tackle social isolation and loneliness among older adults. Furthermore, future studies should consider evaluating social isolation or loneliness while developing customized ICT solutions to provide more robust data on the effectiveness of the solutions.
Conference Paper
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Social agents have been used in games often, for example, to create a social dimension (e.g. the inhabitants of a village) or to provide challenges to players (e.g. the opponents players face). These agents have an essential role in the players’ experience, and, as such, their creation needs to carefully considered. In this paper we propose a taxonomy of social roles that agents can play in games as a step towards the formalization of the problem of the creation of social agents in games. We believe that this taxonomy can help researchers to reach some common ground on the subject and, therefore, promote common views of the research problems involved in the design and development of social agents for games. We discuss several open challenges in the creation of social agents for games and discuss some future directions of research that can be grounded on the analysis of the taxonomy. For instance, many of the social roles proposed are played by agents that do not have much agency or autonomy. Also, there is a large number of under-explored social roles in games at the moment. The taxonomy serves as inspiration to guide game design involving social interactions with game actors, promoting new kinds of gameplay built on the interactive space afforded by the social agents.
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In this video we present a social robotic player that is able to play a traditional card game in a social manner. The interaction takes place in a rich environment in which two teams of two players each compete to win the card game. Therefore, the robotic game player has a partner, and an opponent team of two other players. During each game, the robot explores both competitiveness with the opponent team and cooperation with its partner, conciliating the performance of players and the social dynamics that emerge during the game-play.
Conference Paper
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According to the United Nations World Population Prospects, the world's population is aging. Older adults constitute a fragile part of society, as aging is always accompanied by major psychological and physical challenges. A way to cope with those challenges is to strive for a good Quality of Life (QoL) and contribute to successful aging. Social robots can play an important role in the promotion of QoL by integrating activities with independent-living older adults. Using a qualitative design through a focus group method, this paper aims to present the activities in which independent-living older adults, i.e., older adults that do not depend upon anyone to carry out their activities, require a robot. By understanding the activities where robots can positively influence and contribute to older adults' QoL, we set specific goals for the future research in the field of Human-Robot Interaction (HRI).
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This paper presents a generic and flexible architecture for emotional agents, with what we consider to be the minimum set of functionalities that allows us to implement and compare different appraisal theories in a given scenario. FAtiMA Modular, the architecture proposed is composed of a core algorithm and by a set of components that add particular functionality (either in terms of appraisal or behaviour) to the architecture, which makes the architecture more flexible and easier to extend.
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The Satisfaction With Life Scale (SWLS) was developed to assess satisfaction with the respondent’s life as a whole. The scale does not assess satisfaction with life domains such as health or finances but allows subjects to integrate and weight these domains in whatever way they choose. Normative data are presented for the scale, which shows good convergent validity with other scales and with other types of assessments of subjective well-being. Life satisfaction as assessed by the SWLS shows a degree of temporal stability (e.g., 54 for 4 years), yet the SWLS has shown sufficient sensitivity to be potentially valuable to detect change in life satisfaction during the course of clinical intervention. Further, the scale shows discriminant validity from emotional well-being measures. The SWLS is recommended as a complement to scales that focus on psychopathology or emotional well-being because it assesses an individuals’ conscious evaluative judgment of his or her life by using the person’s own criteria.
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Assistive social robots, a particular type of assistive robotics designed for social interaction with humans, could play an important role with respect to the health and psycho-logical well-being of the elderly. Objectives Assistive social robots are believed to be useful in eldercare for two reasons, a functional one and an affective one. Such robots are developed to function as an interface for the elderly with digital technology, and to help increase the quality of life of the elderly by providing companionship, respectively. There is a growing attention for these devices in the literature. However, no comprehensive review has yet been performed to in-vestigate the effectiveness of such robots in the care of the elderly. Therefore, we systematically reviewed and analyzed existing literature on the effects of assistive social robots in health care for the elderly. We focused in particular on the com-panion function. Data Sources A systematic search of MEDLINE, CINAHL, Psy-cINFO, The Cochrane Library databases, IEEE, ACM libraries and finally Google Scholar was performed for records through December 2007 to identify articles of all studies with actual subjects aimed to assess the effects of assistive social robots on the elderly. This search was completed with information derived from personal expertise, contacts and reports. Study Selection and Data Extraction Since no randomized controlled trials (RCT)'s have been found within this field of research, all studies reporting effects of assistive robotics in elderly popula-tions were included. Information on study design, interventions, controls, and findings were extracted for each article. In medical journals only a few articles were found, whereas about 50 publications were found in literature on ICT and robotics. Data Synthesis The identified studies were all published after 2000 in-dicating the novelty of this area of research. Most of these publications contain the results of studies that report positive effects of assistive social robots on health and psychological well-being of elders. Solid evidence indicating that these ef-fects can indeed be attributed to the actual assistive social robot, its behavior and its functionality is scarce. Conclusions There is some qualitative evidence as well as limited quantitative evidence of the positive effects of assistive social robots with respect to the elderly. The research designs, however, are not robust enough to establish this. Confounding variables often cannot be excluded. This is partly due to the chosen research designs, but also because it is unclear what research methodology is adequate to investigate such effects. Therefore, more work on methods is needed as well as robust, large-scale studies to establish the effects of these devices. Assistive social robots in elderly care: a review G8(2)Review-Broekens-v4.indd 1 29-5-2009 10:52:03
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This article reports the state of advancement of the Robo-Care project, which was launched in December last year to address the problem of providing assistance to elderly people using a combina-tion of software, robots, intelligent sensors and humans. It addresses the creation of a multi-agent environment in which all these actors cooper-ate synergistically in order to provide user services. This paper details two aspects of the system in the making, namely the centralized, service-oriented supervision infrastructure, called Active Supervision Framework (ASF), and the robotic components in use in the present stage of system development. In particular, we give an overview of the integrated plan-ning and scheduling, execution monitoring and diagnosis services offered by the ASF, and on the domestic testbed environment which has been realized in our labs for on-site testing of the integrated system.
Conference Paper
According to the United Nations World Population Prospects, the world’s population is aging. Older adults constitute a fragile part of society, as aging is always accompanied by major psychological and physical challenges. A way to cope with those challenges is to strive for a good Quality of Life (QoL) and contribute to successful aging. Social robots can play an important role in the promotion of QoL by integrating activities with independent-living older adults. Using a qualitative design through a focus group method, this paper aims to present the activities in which independent-living older adults, i.e., older adults that do not depend upon anyone to carry out their activities, require a robot. By understanding the activities where robots can positively influence and contribute to older adults’ QoL, we set specific goals for the future research in the field of Human-Robot Interaction (HRI).
The real challenge of creating believable and enjoyable board game artificial opponents lies no longer in analysing millions of moves per minute. Instead, it lies in creating opponents that are socially aware of their surroundings and that can interact socially with other players. In traditional board games, where face-to-face interactions, social actions and strategic reasoning are important components of the game, artificial opponents are still difficult to design. In this paper, we present an initial effort towards the design of board game opponents that are perceived as socially present and can socially interact with several human players. To accomplish this, we begin by an overview of board game artificial opponents. Then we describe design guidelines for developing empirically inspired social opponents for board games. These guidelines will be illustrated by concrete examples in a scenario where a digital table is used as a user interface, and an intelligent social robot plays Risk against three human opponents.
This study examined the degree of independence between Positive Affect (PA) and Negative Affect (NA) within a given situation. The affective state was measured before and after an experimentally induced success or failure experience in an anagram task. Two types of affect measures were used to assess PA and NA: the Positive and Negative Affect Schedule (PANAS) and a Pleasantness-Unpleasantness scale. Consistent with our hypotheses, results show that PA and NA are independent when measured with the PANAS but are correlated when assessed with the other scale. These PA-NA correlations differed significantly from each other before and after emotion induction, respectively. Additional analyses indicate that both PA scales are differentially sensitive to the mood induction procedure. The findings are discussed with respect to circumplex models of emotion.
Deep Blue is the chess machine that defeated then-reigning World Chess Champion Garry Kasparov in a six-game match in 1997. There were a number of factors that contributed to this success, including: •a single-chip chess search engine,•a massively parallel system with multiple levels of parallelism,•a strong emphasis on search extensions,•a complex evaluation function, and•effective use of a Grandmaster game database.This paper describes the Deep Blue system, and gives some of the rationale that went into the design decisions behind Deep Blue.