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Behavioral comparison of human-animal (dog) and human-robot (AIBO) interactions

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The behavioural analysis of human-robot interactions can help in developing socially interactive robots. The current study analyzes human-robot interaction with Theme software and the corresponding pattern detection algorithm. The method is based on the analysis of the temporal structure of the interactions by detecting T-patterns in the behaviour. We have compared humans' (children and adults) play behaviour interacting either with an AIBO or a living dog puppy. The analysis based on measuring latencies and frequencies of behavioural units suggested limited differences, e.g. the latency of humans touching the dog/AIBO was similar. In addition other differences could be accounted for by the limited abilities of the robot to interact with objects. Although the number of interactive T-patterns did not significantly differ among the groups but the partner's type (whether humans were playing with dog or AIBO) had a significant effect on the structure of the patterns. Both children and adults terminated T-patterns more frequently when playing with AIBO than when playing with the dog puppy, which suggest that the robot has a limited ability to engage in temporally structured behavioural interactions with humans. As other human studies suggest that the temporal complexity of the interaction is good measure of the partner's attitude, we suggest that more attention should be paid in the future to the robots' ability to engage in cooperative interaction with humans.
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Behavioural Processes 73 (2006) 92–99
Behavioural comparison of human–animal (dog)
and human–robot (AIBO) interactions
A. Kerepesi a,b,, E. Kubinyib, G.K. Jonsson c,d, M.S. Magnusson c,´
A. Mikl´
osi b
aComparative Ethology Research Group, Hungarian Academy of Sciences, Budapest, Hungary
bDepartment of Ethology, E¨otv¨os University, Budapest, Hungary
cHuman Behaviour Laboratory, University of Iceland, Iceland
dDepartment of Psychology, University of Aberdeen, Scotland, United Kingdom
Received 24 October 2005; received in revised form 27 March 2006; accepted 1 April 2006
Abstract
The behavioural analysis of human–robot interactions can help in developing socially interactive robots. The current study analyzes human–robot
interaction with Theme software and the corresponding pattern detection algorithm. The method is based on the analysis of the temporal structure
of the interactions by detecting T-patterns in the behaviour. We have compared humans’ (children and adults) play behaviour interacting either
with an AIBO or a living dog puppy.
The analysis based on measuring latencies and frequencies of behavioural units suggested limited differences, e.g. the latency of humans touching
the dog/AIBO was similar. In addition other differences could be accounted for by the limited abilities of the robot to interact with objects.
Although the number of interactive T-patterns did not significantly differ among the groups but the partner’s type (whether humans were playing
with dog or AIBO) had a significant effect on the structure of the patterns. Both children and adults terminated T-patterns more frequently when
playing with AIBO than when playing with the dog puppy, which suggest that the robot has a limited ability to engage in temporally structured
behavioural interactions with humans.
As other human studies suggest that the temporal complexity of the interaction is good measure of the partner’s attitude, we suggest that more
attention should be paid in the future to the robots’ ability to engage in cooperative interaction with humans.
© 2006 Elsevier B.V. All rights reserved.
Keywords: Human–animal interaction; Human–robot interaction; Temporal patterns
1. Introduction
People interact with computers and computerized machines,
and such systems are part of our everyday life. Personal com-
puters are common in most households, and some predict (e.g.
Bartlett et al., 2004) that robots will be as widespread in the not
too distant future as PCs are today. While some robotic systems
have no or just some degree of autonomy, others are able to
work without the presence of a human (for examples see Agah,
2001). Although autonomous robots were originally designed to
work independently from humans, nowadays many such robots
are around us and we are interacting with them. A new genera-
tion of autonomous robots, the so-called entertainment robots,
are designed specially to interact with people. Some of them
Corresponding author. Tel.: +36 1 381 2179; fax: +36 1 381 2180.
E-mail address: akerepesi@yahoo.com (A. Kerepesi).
are functioning as physical aids for elderly people (Pineau et
al., 2003), as museum-guide robots (Nourbakhsh et al., 1999;
Burgard et al., 1999), as educational instruments (Billard, 2003),
or as therapeutic tools (Dautenhahn and Werry, 2002).
Other types of such autonomous robots are designed to pro-
vide some kind of “entertainment” for the human, and have
the characteristics to induce an emotional relationship (“attach-
ment”) (Donath, 2004; Kaplan, 2001). One of the most popular
entertainment robots is Sony’s AIBO (Pransky, 2001) which is
to some extent reminiscent to a dog–puppy. AIBO is equipped
with a sensor for touching, it is able to hear and recognize its
name and up to 50 verbal commands, and it has a limited abil-
ity to see pink objects. It produces vocalisations for expressing
its ‘mood’, in addition it has a set of predetermined action pat-
terns like walking, paw shaking, ball chasing, etc. Although it
is autonomous, the behaviour of the robot depends also on the
interaction with the human partner. AIBO is able to learn and
can be trained with “clicker training” (Kaplan et al., 2002).
0376-6357/$ – see front matter © 2006 Elsevier B.V. All rights reserved.
doi:10.1016/j.beproc.2006.04.001
A. Kerepesi et al. / Behavioural Processes 73 (2006) 92–99 93
To investigate humans’ interaction with entertainment robots
two different approaches have been preferred. Based on surveys
some researchers are trying to find out whether humans perceive
AIBO as similar to a dog and what kind of emotions they ascribe
to the robot. A content analysis of online postings to a chatroom
for AIBO owners focused on describing owners’ perceived rela-
tionship with their AIBOs (Kahn et al., 2003). About 42% of the
participants spoke of AIBO having feeling while 26% of them
spoke of AIBO as a companion. Kahn et al. (2003) suggested
that the relationship between people and their AIBO appeared to
be similar to the relationship people have with live dogs. When
comparing children’s attitudes towards AIBO and other robots
Bartlett et al. (2004) found that children referred to AIBO as if
it were a living dog, labelled it as “robotic dog” and used rather
‘he’ or ‘she’ than ‘it’ when talked about AIBO. Interviewing
children Melson et al. (2004) found that although they distin-
guished AIBO from a living dog, they attributed psychological,
companionship and moral stance to the robot. Interviewing older
adults Beck et al. (2004) found that elderly people regarded
AIBO much like as a family member and they attributed animal
features to the robot.
The second line of studies is concerned with the observa-
tion of robot–human interactions based on ethological methods
of behaviour analysis. Comparing children’s interaction with
AIBO and a stuffed dog Kahn et al. (2004) found that chil-
dren distinguished between the robot and the toy. Although they
engaged in imaginary play with both of them, they showed more
exploratory behaviour and attempts at reciprocity when playing
with AIBO. Turner et al. (2004) found that children touched the
live dog over a longer period than the robot but ball game playing
was more frequent with AIBO than with the dog puppy.
Although these observations show that people distinguish
AIBO from non-living objects, the results are somehow contro-
versial. While questionnaires and interviews suggest that people
consider AIBO as a companion and view it as a family mem-
ber, their behaviour suggest that they differentiate AIBO from a
living dog.
To investigate whether humans interact with AIBO as a
robotic toy rather than real dog, one should analyze their interac-
tion pattern in more detail. To analyze the structural differences
found in the interaction between human and AIBO and human
and a living dog we propose to analyze the temporal struc-
ture of these interactions. The THEME program (PatternVision
Ltd.) allows the analyst to detect complex repeated temporal
patterns even when a multitude of unrelated events occur in
between components of the patterns, which typically makes
them undetectable for currently available statistical methods
(for theoretical foundation and explanation of the model and
method see Magnusson, 1996, 2000; Anolli et al., 2005, and see
also www.hbl.hi.is). The production and perceptual detection of
such patterns may well constitute important social skills to be
considered in studies of, for example, human social handicaps
and “social” robotics (Magnusson, 2004).
In a previous study investigating cooperative interactions
between the dog and its owner (Kerepesi et al., 2005), we found
that their interaction consists of highly complex patterns in time,
and these patterns contain behaviour units, which are important
in the completion of a given task. Analyzing temporal patterns
in behaviour proved to be a useful tool to describe dog–human
interaction. Based on our previous results (Kerepesi et al., 2005)
we assume that investigating temporal patterns can not only pro-
vide new information about the nature of dog–human interaction
but also robot–human interaction.
In our study we investigated children’s and adults’ behaviour
during a play session with AIBO and compared it to playing with
a living dog puppy. Our focus was on analyzing spontaneous play
between the human and the dog–robot. We wanted to: (1) analyze
and compare the temporal structure of the interaction with dog
and AIBO in both children and adults, and (2) to investigate
whether there are any differences in their play behaviour.
2. Methods
2.1. Subjects
Twenty-eight adults and 28 children were divided into four
experimental groups:
1. Adults playing with AIBO: seven males and seven females
(mean age: 21.1 years, S.D. = 2.0 years), eight of them has or
had a dog before, six of them never had a dog.
2. Children playing with AIBO: seven males and seven females
(mean age: 8.2 years, S.D. = 0.7 years), four of them has or
had a dog before, five of them never had a dog, five of them
did not answer this question.
3. Adults playing with dog: seven males and seven females
(mean age: 21.4 years, S.D. = 0.8 years), nine of them has
or had a dog before, five of them never had a dog.
4. Children playing with dog: seven males and seven females
(mean age: 8.8 years, S.D. = 0.8 years), six of them has or
had a dog before, eight of them never had a dog.
5. The number of dog owners in a group did not differ signifi-
cantly.
2.2. Procedure
The test took place in a 3 m ×3 m separated area of a
room. Children were recruited from elementary schools, and
the tests were in their schools in a familiar room but not their
classroom. Adults were university students, and the tests were
carried out either in a familiar room at their dormitory (adult-
AIBO dyads) or a familiar room at the university (adult-dog
dyads). The robot was Sony’s AIBO ERS-210 (dimension:
154 mm ×266 mm ×274 mm; mass: 1.4kg; colour: silver) that
is able to recognize and approach pink objects. To generate a
constant behaviour, the robot was used only in its after-booting
period for the testing. During the booting period the robot was
lying and wiggled its head. The robot’s booting behaviour was
the same in each case, neither the latency of standing up nor the
behaviour units recorded during the booting differed in children-
AIBO and adult-AIBO dyads After the booting period the robot
was put down on the floor, and it “looked around” (turned its
head), noticed the pink object, stood up and approached the ball
(“approaching” meant several steps toward the pink ball). If the
94 A. Kerepesi et al. / Behavioural Processes 73 (2006) 92–99
robot lost the pink ball it stopped and “looked around” again.
When it reached the goal-object, it started to kick it. If stroked,
the robot stopped and started to move its head in various direc-
tions.
The dog puppy was a 5-month-old female Cairn terrier, sim-
ilar size to the robot. It was accustomed to interacting with both
children and adults, furthermore, its owner’s age was similar
to the children participating in the test. It was playful and its
behaviour was not controlled in rigid manner during the playing
session. When the dog seemed to be exhausted we stopped the
test and continued next day.
The toy for AIBO was its pink ball, and a ball and a tug for
the dog puppy. The tug was introduced in this situation in order
to motivate the dog puppy for more play.
The participants played for 5 min either with AIBO or the dog
puppy in a spontaneous situation. None of the participants had
met the test partners before the playing session. At the beginning
of each play we asked participants to play with the dog/AIBO
for 5 min, and informed them that they could do whatever they
wanted, in the sense that the participants’ behaviour were not
controlled in any way. All participants were told that AIBO was
designed to like being stroked and playing with a pink ball.
However, they were not told where the sensors were. About the
dog puppy the experimenter said that she can be stroked and
likes playing with either the ball or the tug.
2.3. Analysis of behaviour
The video recorded play sessions were coded by Theme-
Coder, which enables detailed transcription of digitized video
files. All the behaviour of AIBO, the dog and the human was
described by 8, 10 and 7 behaviour units, respectively (for the list
of the behaviour units see Appendix A). Only those behaviour
units were included in this study that were present in all groups,
and (due to statistical reasons) occurred at least in two dyads in
each group (see Table 1).
Three aspects of the interaction were analyzed. Play
behaviour consists of behaviour units referring to play or
attempts to play, such as dog/AIBO approaches toy, orientation
to the toy and human moves the toy. The partners’ activity during
play includes dog/AIBO walks, stands, lies and approaches the
toy. Interest in the partner includes humans’ behaviour towards
the partner and can be described by their stroking behaviour and
orientation to the dog/AIBO.
We have also noted the latency of the first human tactile
contact (touch) with the dog/AIBO. (This was also the start-
ing point of the 2-min long observation period, transcribed by
ThemeCoder, as we expected interactive behaviour elements
to occur more frequently after the humans first touched the
dog/robot.) Previous work has shown that 2min (3000 digitized
video frames) provides sufficient duration for time pattern anal-
ysis.
2.4. Theme software
The interactions were transcribed using ThemeCoder and
the transcribed records were then analyzed using Theme 5.0
(see www.patternvision.com). The basic assumption of this
methodological approach, embedded in the Theme 5.0 soft-
ware, is that the temporal structure of a complex behavioural
system is largely unknown, but may involve a set of par-
ticular type of repeated temporal patterns (T-patterns) com-
posed of simpler directly distinguishable event-types, which
are coded in terms of their beginning and end points (such as
“dog begins walking” or “dog ends orienting to the toy”). The
kind of behaviour record (as set of time point series or occur-
rence times series) that results from such coding of behaviour
within a particular observation period (here called T-data)
constitutes the input to the T-pattern definition and detection
algorithms.
Essentially, within a given observation period, if two actions,
A and B, occur repeatedly in that order or concurrently, they
are said to form a minimal T-pattern (AB) if found more often
than expected by chance, assuming as h0 independent distribu-
tions for A and B, there is approximately the same time distance
(called critical interval, CI) between them. Instances of A and
B related by that approximate distance then constitute occur-
rence of the (AB) T-pattern and its occurrence times are added
to the original data. More complex T-patterns are consequently
gradually detected as patterns of simpler already detected pat-
terns through a hierarchical bottom-up detection procedure.
Pairs (patterns) of pairs may thus be detected, for example
((AB)(CD)), (A(KN))(RP)), etc. Special algorithms deal with
potential combinatorial explosions due to redundant and par-
tial detection of the same patterns using an evolution algorithm
(completeness competition), which compares all detected pat-
terns and lets only the most complete patterns survive. As any
basic time unit may be used, T-patterns are in principle scale-
Table 1
Behaviour units used in this analysis
Play behaviour Activity Interest in partner
Abbreviation Description Abbreviation Description Abbreviation Description
Look toy Dog/AIBO orients to
toy
Stand Dog/AIBO stands Stroke Human strokes the dog/AIBO
Approach toy Dog/AIBO
approaches toy
Lie Dog/AIBO lies Look dog Human looks at dog/AIBO
Move toy Human moves the toy
in front of dog/AIBO
Walk Dog/AIBO walks (but not
towards the toy)
Approach toy Dog/AIBO approaches
toy
A. Kerepesi et al. / Behavioural Processes 73 (2006) 92–99 95
Fig. 1. An example for an interactive T-pattern. This pattern was detected in an adult-AIBO dyad. The upper left box shows the events occurring within the pattern,
listed in the order in which they occur within the pattern. The first event in the pattern appears at the top and the last at the bottom. The upper right box shows
the frequency of events within the pattern, each dot means that an event has been coded. The pattern diagram (the lines connecting the dots) shows the connection
between events. The number of pattern diagrams illustrates how often the pattern occurs. Subpatterns also occur when some of the events within the pattern occur
without the whole of the pattern occurring. The lower box illustrates the real-time of the pattern. The lines show the connections between events, when they take
place and how much time passes between each event.
independent, while only a limited range of basic unit size is
relevant in each concrete study.
2.5. Data analysis
During the coding procedure we recorded the frequency and
the duration of behavioural units. We have also transcribed the
latency of the first human tactile contact with the dog/AIBO (this
was also the starting point of the 2-min long coding with Theme-
Coder). Concerning the search for temporal patterns (T-patterns)
we used, as a search criterion a minimum two occurrences in
the 2-min period for each pattern type, the tests for CI was set
at p= 0.005, and only included interactive patterns (those T-
patterns which contain both the human’s and the dog’s/AIBO’s
behaviour units; for example of a T-pattern see Fig. 1). The num-
ber, length and level of interactive T-patterns were analyzed with
a special focus on whether the human or the dog/AIBO initial-
ized and terminated the T-pattern more frequently. A T-pattern
is initialized/terminated by human if the first/last behaviour unit
in that pattern is the human’s. A comparison between the ratio of
T-patterns initiated or terminated by humans, in the four groups,
was carried out as well as the ratio of those T-patterns containing
behaviour units listed in Table 1. Tests were also conducted on
the effect of the subjects’ age (children versus adults) and the
partner type (dog puppy versus AIBO) using two-way ANOVA.
3. Results
The overall difference in the latency of the first touch
of the dog/AIBO among the four groups was not significant
(F3,56 = 2.24, p= 0.095). Similarly the overall difference in the
duration of behaviour units referring to humans’ interest in the
partner was not significant. The time spent stroking and looking
to the dog/AIBO did not differ among the groups.
Comparing the duration of the behaviour units associated
with playing we have found that the overall duration of approach
toy differed among the groups (F3,56 = 7.44, p< 0.001) with the
significant effect of the partner’s type (F1,56 = 17.43, p< 0.001).
AIBO spent more time approaching the toy, when playing with
children, while no such difference was found when adults played
with the dog puppy or AIBO. Humans’ age had an effect on
the duration of look at toy (F3,56 = 5.21, p= 0.003, effect of
age: F1,56 = 10.96, p= 0.002). Both the dog and AIBO spent
more time orienting to the toy when playing with children. The
duration of move toy varied significantly among the groups
(F3,56 = 8.83, p< 0.001), with the significant effect of partici-
pants’ age. Adults also spent more time moving the ball in front
of the dog/AIBO than children did when playing with either
AIBO or dog (F1,56 = 4.35, p= 0.042). However, both children
and adults spent more time moving the toy if they were playing
with AIBO (F1,56 = 21.92, p< 0.001). No significant interaction
was found between the effect of humans’ age and the partner’s
type (Fig. 2).
Humans’ age also had a significant effect on the dog/AIBO’s
activity during the playing session. The dog puppy spent more
time with lying on the floor (F3,56 = 5.89, p= 0.002, ‘human age’
F1,56 = 4.73, p= 0.002), and less time with standing and walking
than AIBO (F3,56 = 8.94, p< 0.001, ‘human age’ F1,56 = 21.167,
p< 0.001 and F3,56 = 7.86, p< 0.001, ‘human age’ F1,56 = 4.75,
p< 0.001, respectively).
96 A. Kerepesi et al. / Behavioural Processes 73 (2006) 92–99
Fig. 2. Mean duration of behaviour units displayed by AIBO or dog (look toy,
approach toy) or humans (move toy)(letters ‘a’, ‘b’ and ‘c’ are indicating whether
the groups differ significantly. Bars marked by the same letter indicate no dif-
ferences between those groups).
The frequency of the behaviour units describing playing
behaviour also differed. Approach toy occurred more frequently
when adults played with the dog puppy than in any other
case (F3,56 = 6.65, p= 0.001). Both the age of the humans
(F1,56 = 4.70, p= 0.035) and the partner (F1,56 = 6.18, p= 0.016)
had significant effects and the interaction between them was also
significant (F1,56 = 9.09, p= 0.004). However the frequency of
look toy did not vary among the groups.
Humans’ age also had an effect on the activity of the play.
The frequency of lie (F3,56 = 2.91, p= 0.043, effect of age:
F1,56 = 4.73, p= 0.034) and walk (F3,56 = 5.99, p= 0.001, effect
of age: F1,56 = 12.25, p< 0.001), were higher in children’s play
(Fig. 3). Both AIBO and the dog lay down and started to walk
around in the room more frequently when playing with children
then when playing with adults.
None of the human’s behaviour (move toy, look dog and
stroke) differed in frequency among the groups.
The number of different interactive T-patterns was on an aver-
age 7.64 (S.D. = 4.94) in adult-AIBO dyads, 3.72 (S.D. = 1.89)
in child-AIBO dyads, 10.50 (S.D. = 10.02) in adult-dog dyads
and 18.14 (S.D. = 25.22) in child dog-dyads. Their number did
not differ significantly among the groups.
Comparing the ratio of T-patterns initialized by humans
among the groups, we have found that adults initialized T-
patterns more frequently when playing with dog than partic-
Fig. 3. Mean frequency of behaviour units displayed by AIBO or dog (letters ‘a’,
‘b’ and ‘c’ are indicating whether the groups differ significantly. Bars marked
by the same letter show that those groups do not differ significantly).
Fig. 4. Mean ratio of interactive T-patterns initiated and terminated by humans
(letters ‘a’ ‘b’ and ‘c’ are indicating whether the groups differ significantly. Bars
marked by the same letter show that those groups do not differ significantly).
ipants of the other groups (F3,56 = 5.27, p= 0.003). Both the
age of the human (F1,56 = 10.49, p= 0.002) and the partner’s
type (F1,56 = 4.51, p= 0.038) had a significant effect, but their
interaction was not significant. The partner’s type (F1,56 = 10.75,
p= 0.002) also had a significant effect on the ratio of T-patterns
terminated by humans (F3,56 = 4.45, p= 0.007) we have found
that both children and adults terminated the T-patterns more fre-
quently when they played with AIBO than when they played
with the dog puppy (Fig. 4).
The age of the human had a significant effect on the ratio
of T-patterns containing approach toy (F1,56 = 4.23, p= 0.045),
and the interaction with the partner’s type was significant
(F1,56 = 6.956, p= 0.011). This behaviour unit was found more
frequently in the T-patterns of adults playing with dog than in
the children’s T-patterns when playing with dog. The ratio of
look toy in T-patterns did not differ among the groups (Fig. 5).
The ratio of the behaviour unit stand also varied among the
groups (F3,56 = 6.59, p< 0.001), there was a lower frequency of
such T-patterns when children were playing with dog than in
any other case (F1,56 = 7.10, p= 0.010). However, the ratio of
behaviour units lie and walk in T-patterns did not differ among
the groups.
The ratio of humans’ behaviour units in T-patterns (move toy,
look dog and stroke) did not vary among the groups.
Fig. 5. Mean ratio of interactive T-patterns containing the behaviour units dis-
played by AIBO or dog (look toy, approach toy) or humans (move toy) (letters
‘a’, ‘b’ and ‘c’ are indicating whether the groups differ significantly.Bars marked
by the same letter show that those groups do not differ significantly).
A. Kerepesi et al. / Behavioural Processes 73 (2006) 92–99 97
4. Discussion
Previous questionnaire studies on human–robot interaction
showed that people describe their relationship with AIBO simi-
lar to a relationship with dog puppy (Kahn et al., 2003), attribute
animal characteristics to the robot and view it as a family mem-
ber (Beck et al., 2004). However, the analysis of their behaviour
tended to show that in parallel they also behave differently
toward the AIBO and a living dog puppy (Turner et al., 2004).
Considering the behavioural pattern of the humans our results
show that neither the latency of the first tactile contact between
humans and the dog/AIBO nor the duration of stroking the
dog/AIBO differed significantly among the groups. This sug-
gests that under the present conditions the robot was as an
affective playing partner for both children and adults as the dog
puppy. Comparing the play behaviour during the interactions we
have found that the only difference between behaviour units per-
formed by humans was the amount of time spent moving the toy
in front of the partner. Both children and adults moved the toy in
front of AIBO for longer duration. This can be explained on the
basis of behavioural difference between the dog and the robot.
The dog spent less time approaching the toy compared to AIBO
because it was faster to get to the toy, and thus there was no need
for the human participants to move the toy so long in front of the
dog puppy in order to get its attention as in front of AIBO. So
the only difference in humans’ behaviour caused by the partner’s
type can be easily explained by AIBO’s much slower movements
compared to the dog puppy. This finding is interesting because
living dogs distinguished AIBO from a dog puppy in a series
of observations by Kubinyi et al. (2004). Those results showed
that both juvenile and adult dogs differentiate between the liv-
ing puppy and AIBO, although their behaviour depended on the
similarity of the robot to a real dog as the appearance of the
AIBO was manipulated systematically.
Considering the behavioural patterns of the play partners both
the dog and the AIBO oriented to the toy more often when play-
ing with children. The dog puppy lay down more often and for
longer periods when playing with children, and it was less active
during the play with children than with adults. The dog puppy
also started to walk around in the room more frequently during
the interaction with adults, while no such difference was found
when adults or children played with AIBO. These findings sug-
gest that children were less successful in motivating the dog
puppy to play than adults.
The results of the traditional ethological analysis showed that
both the subjects’ age and the partner’s type have a significant
effect on the interaction. The behaviour of the dog and AIBO
(their activity and playing behaviour) were different depending
on their type (dog or AIBO) and the age of the subjects’ with
whom they were playing (children or adults). However, the only
difference we have found in humans’ behaviour caused by the
partner can be explained by the faster speed of movements in
the dog puppy compared to the AIBO and not on the basis of
the difference between the robot and the living dog puppy.
To investigate whether humans interact with AIBO as a non-
living toy rather than a living dog, we have analyzed the temporal
patterns of these interactions. We have found that similarly
to human interactions (Borrie et al., 2002; Magnusson, 2000;
Grammer et al., 1998) and human–animal interactions (Kerepesi
et al., 2005), human–robot interactions also consist of complex
temporal patterns. In addition the numbers of these temporal pat-
terns are comparable to those T-patterns detected in dog–human
interactions in similar contexts.
One important finding of the present study was that the
type of the play partner affected the initialization and termina-
tion of T-patterns. Adults initialized T-patterns more frequently
when playing with dog while T-patterns terminated by a human
behaviour unit were more frequent when humans were playing
with AIBO than when playing with the dog puppy. In principle
this finding has two non-exclusive interpretations. In the case of
humans the complexity of T-patterns can be affected by whether
the participants liked the partner with whom they were inter-
acting or not (Grammer et al., 1998; Sakaguchi et al., 2005).
This line of argument would suggest that the distinction is based
on the differential attitude of humans toward the AIBO and the
dog. Although, we cannot exclude this possibility, it seems more
likely that the difference has its origin in the play partner. The
observation that the AIBO interrupted the interaction more fre-
quently than the dog suggests that the robot’s actions were less
likely to become part of the already established interactive tem-
poral pattern. This observation can be explained by the robot’s
limited ability to recognize objects and humans in its environ-
ment. AIBO is only able to detect a pink ball and approach it.
If it losses sight of ball it stops and that can interrupt the play-
ing interaction with the human. In contrast, the dog’s behaviour
is more flexible and it has a wider ability to recognize human
actions, thus there is an increased chance for the puppy to com-
plement human behaviour.
From the ethological point of view it should be noted that
even in natural situations dog–human interactions have their
limitations. For example, analyzing dogs’ behaviour towards
humans, Rooney et al. (2001) found that most of the owner’s
action trying to initialize a game remains without reaction. Both
Millot and Filiˆ
atre (1986);Millot et al. (1988) and Filiˆ
atre et al.
(1986) demonstrated that in child–dog play the dog reacts only
at approximately 30% of the child’s actions, while the child
reacts to 60% of the dog’s actions. Although in the case of play
it might not be so important, other situations in the everyday
life of both animals and man require some level of temporal
structuring when two or more individuals interact. Such kinds
of interactions have been observed in humans performing joint
tasks and in the case of guide dogs and their owners. Naderi et
al. (2001) found that both guide dogs and their blind owners ini-
tialize actions during their walk, and sequences of initializations
by the dog are interrupted by actions initialized by the owner.
Although the results of the traditional ethological analysis
both in our own and other studies (e.g. Kahn et al., 2004; Bartlett
et al., 2004) suggest that people interact with AIBO in some ways
as if it were a living dog puppy, and that playing with AIBO can
provide a more complex interaction than a simple toy or remote
controlled robot, the analysis of temporal patterns revealed some
differences. Although we did not investigated this in the present
study the differences in initialization and termination of the inter-
actions could have a significant effect on the human’s attitude
98 A. Kerepesi et al. / Behavioural Processes 73 (2006) 92–99
toward their partner, that is, in the long term humans could get
“bored” or “frustrated” when interacting with a partner that has
a limited capacity to being engaged in temporally structured
interactions.
In summary, contrary to the findings of previous studies, it
seems that at a more complex level of behavioural organisation,
human–AIBO interaction is still different from the interactions
displayed while playing with a real puppy, and in the future more
attention should be paid to the temporal aspects of behavioural
pattern when comparing human–animal versus human–robot
interaction.
Acknowledgements
This work has been supported by OTKA (T043763), and a
grant from the HAS (F01/031). We would like to thank Frederic
Kaplan for providing the AIBO for this study and M´
arta G´
acsi
one of the owners of the dog puppy (Nudli) for her help in
collecting of the data.
Appendix A
List of the coded behaviour units. Behaviour units written in
italics are part of this analysis
(a) Behaviour units in AIBO
Orientation to toy (look toy)
Stand
Sit
Lie
Move its head
Walk (but not towards the toy)
Approach toy
Raise its paw
(b) Behaviour units in dog puppy
Orientation to human
Orientation to toy (look toy)
Stand
Sit
Lie
Walk (but not towards the toy)
Approach toy
Try to leave the room
Chew toy
Chew human
(c) Behaviour units in humans
Orientation to toy
Orientation to dog (look dog)
Stand
Sit or squat
Move the toy in front of the dog/AIBO (move toy)
Stroke the dog/AIBO (stroke)
Flinch back
Speaking to the dog/AIBO
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Play signals are known to function in the solicitation and maintenance of intraspecific play, but their role in interspecific play is relatively unstudied. We carried out two studies to examine interspecific signalling when humans play with domestic dogs, Canis familiaris. In the first, we recorded dog–owner play sessions on video to identify actions used by 21 dog owners to initiate play with their dogs. Thirty-five actions were each used by three or more owners. These included postures, vocalizations and physical contact with the dog. The actions varied greatly in their apparent success at instigating play which was, surprisingly, unrelated to the frequency with which they were used. We then did an experiment to determine the effect of composites of commonly used signals upon the behaviour of 20 Labrador retrievers. The performance of both ‘Bow’ and ‘Lunge’ by a human altered the subsequent behaviour of the dogs. Both signals caused increases in play, and Lunge produced significant increases in play bout frequency and mean bout duration. The efficiency of both these postural signals was enhanced when they were accompanied by play vocalizations. Thus, specific actions used by humans do communicate a playful context to dogs and can be described as interspecific play signals.
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In two studies, we have investigated the co-operative behaviour between dogs and their owners. We supposed that co-operative behaviour is an inherited trait in dogs, and is a major contributing factor in the development of successful guide dog performance. According to our view, leading a blind person involves complex behaviour where success depends on the ability of the participants to synchronise their actions. In Study I, we observed both British and Hungarian blind owners taking a half-hour walk in their neighbourhood. In Study II, both guide dogs with their blind and pet dogs with their blind-folded owners had to master an obstacle course. Measuring the frequency of initiations of various actions during leading their owners, dogs did not keep the role of the initiator to themselves. However, both dogs and humans were found to initiate more often in some types of actions, for example, guide dogs initialised avoidance or stepping up more often than their owners. Further, the role of the initiator was kept only for short durations, longer sequences of initialising were rare.Despite many differences among groups studied, we observed some qualitative similarities in the co-operative behaviour of dogs. We assume that during domestication, dogs have been selected for the ability to change to-and-fro the role of the initiator that seems to be fundamental in this type of co-operation. In the case of leading the blind, information should not only be provided but also accepted by both parties in the course of the joint actions, therefore, the leadership (the role of the initiator) may vary form one action to the next.
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This study is based on the analysis of video films of spontaneous actions between children from 2 to 5 years of age and their pet dog (N = 20), and presents behavioural sequences which regulate the interactions between the child and his dog. The preliminary results indicate and compare the percentages of the different communication behaviours of the child and dog, and the behavioural modifications which followed. The discussion deals with the originality of the child-dog communication systems as compared with the relational systems of a young child with his peers.
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Sony’s AIBO entertainment robot has broken all records for the number of robots sold in the shortest time period. The AIBO is an autonomous home entertainment robot with artificial intelligence. Its behavior simulates a dog’s in its ability to walk and play, with built-in functions for emotions, instincts, learning and growth. Yet AIBO was not intended by Sony to be a dog substitute, but to further the man-robot interaction. It has received an overwhelming response worldwide and it appears as if AIBO may be just the beginning of Sony’s home entertainment robots.