CHI 2008 Proceedings · Works In Progress

April 5-10, 2008 · Florence, Italy

Effect of Agent Appearance on
People’s Interpretation of Agent’s
AttitudeTakanori Komatsu

Abstract

Shinshu University.

We conducted psychological experiments in which
participants were presented with artificial sounds thatwere intended to convey the attitudes of three different
agents: a Mindstorms robot, an AIBO, and a laptop PC.
The participants were asked to select the correct
attitudes based on the sounds expressed by these threeagents. The results showed that the participants had
higher interpretation rates when the PC presented thesounds, even though the utilized artificial sounds werethe same for all three agents.

3-15-1 Tokida, Ueda.
Nagano 386-8567, JAPANtkomat@shinshu-u.ac.jp
Seiji Yamada
National Institute of Informatics.
2-1-2 Hitotsubashi, Chiyoda.
Tokyo 101-8430, JAPANseiji@nii.ac.jp

Keywords
Agent appearance, agent attitudes, human-agent
interaction

ACM Classification Keywords
J.4 [Computer Applications]: Social and Behavioral
Sciences–Psychology.

Introduction

Copyright is held by the author/owner(s).
CHI 2008, April 5-10, 2008, Florence, Italy.
ACM 978-1-60558-012-8/08/04.

One of the hottest topics in human-agent interaction
studies is determining what appearance an agent
should have in order to interact with people effectively.
People are said to build in their minds agent behavior
models based on the agent’s appearance; that is, theagents’ appearance significantly affects the interaction

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CHI 2008 Proceedings · Works In Progress[1]. For example, when people encounter a dog-likerobot, they expect dog-like behaviors from the robot,
and they would naturally speak to it using verbal
commands such as “sit” and “lie down.” In contrast,
they would not act this way toward a cat-like robot.
Several studies have focused on how an agent’s
appearance affects its interactions with people [2,3].
On the basis of these studies, we are focusing on theissues of what the agent’s appearance should be inorder to interact with people effectively and what kindof information agents should express to people. As thefirst step in this research, we investigated how peopleinterpreted presented information to see if they could
determine the attitudes of agents that have differentappearances.

Agents’ attitudes, appearances, andexpressed information
We experimentally investigated the basic psychologicalrelationship between the appearance of an agent andthe information it expresses on how people interpret its
attitudes.
We selected positive and negative attitudes
corresponding to valence values as primitive attitudes
for the agents to express. If agents are to interact
effectively with people they should be able to convey
these two values [4].
Next, we utilized artificial sounds that did not include
any verbal information, but were simple and intuitivefor informing people about the agents’ primitiveattitudes. Komatsu [5] experimentally showed thatpeople can estimate different primitive attitudes bymeans of simple beep-like sounds with different
durations and inflections. We selected this kind ofApril 5-10, 2008 · Florence, Italy

information because of the technical ease of
implementation into the agents.
We selected three agents having different appearances:a Mindstorms robot (LEGO Corporation), an AIBO robot(SONY Corporation), and a normal laptop PC (Let’s note
W2, Panasonic Inc.).

Preliminary Experiment
We conducted a preliminary experiment to determine
artificial sounds that were effective in evoking positiveor negative attitudes from people.
We prepared 44 different types of triangle wave soundswith four different durations and 11 different F0contours (F0 average: 131 Hz). The four durations
were 189, 418, 639, and 868 ms. The 11 F0 contours
were set so that the transition range of F0 values
between the onset and endpoint of the sound stimuli
were 0, ±25, ±50, ±75, ±100, or ±125 and werelinearly downward or upward. These sounds had a tone
like a computer beep. The sound stimuli labeled“189u25” indicates that duration was 189 ms and theF0 transition range was 25 Hz with an upward slope(increasing intonation).
The participants were 10 Japanese university students(6 men and 4 women; 19 – 23 years old). One
randomly selected sound among the 44 preparedsounds was presented to the participants. Afterwards,
the participants were asked to select the correct one ofthree attitudes as follows: 1) Positive: the PC’s internal
state appeared to be good, 2) Negative: the PC’sinternal state appeared to be bad, and 3)
Undistinguishable: it was unclear whether the PC’sinternal state was positive or negative. Each participant

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CHI 2008 Proceedings · Works In Progress

April 5-10, 2008 · Florence, Italy

heard all 44 prepared sounds. The order of the sounds
was counterbalanced for all 10 participants. The sounds
were presented on a normal laptop PC.
The results of this preliminary experiment showed thatall 10 participants believed the PC had positive
attitudes for four sounds: 189u125, 418u125, 639u125,and 868u125. Also, all participants believed the PC had
negative attitudes for four sounds: 418d25, 418d50,418d75, and 639d50. These eight sounds were selected
for the next experiment.

ExperimentThis experiment investigated the effect of an agent’s
appearance on how participants interpreted its attitudes.
The participants were presented with the sounds that
had been selected in the preliminary experiment byagents with different appearances; a Mindstorms robot,
an AIBO, and a normal laptop PC (see Figure 1). They
were then asked to select the correct attitudes (positive,negative, or undistinguishable) based on the sounds
made by these three agents.
The participants were 20 Japanese university students(17 men and 3 woman; 19 – 24 years old); they were
not familiar with robots or the toys and had notparticipated in the preliminary experiment. First, theparticipants were told that the task of this experiment
was to select one of three attitudes (positive, negative,or undistinguishable) based on the sounds the agentsmade. All participants experienced the following threeconditions.

Figure 1. AIBO robot, Mindstorms robot, and laptop PC.

1.

Eight sounds expressed by the Mindstorms robot(MS condition): the eight sounds came from an
FM radio tuner placed on the Mindstorms robot.
This radio tuner received sounds transmitted fromthe sound-expressing PC indicated in Figure 2.

2.

Eight sounds expressed by AIBO (AIBOcondition): the sounds were presented using
AIBO’s “AIBO entertainment player” software thatwas installed in the AIBO-operating PC.

3.

Eight sounds expressed by the laptop PC (PCcondition): This laptop PC was remotely operated
by the sound-expressing PC.

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CHI 2008 Proceedings · Works In ProgressApril 5-10, 2008 · Florence, Italy

Wireless LAN（Remote Access via Real VNC）
FM radio wave)

FM radio tuner

Wireless LAN （motion command）

FMTransmitter
AIBOSound
AIBO
Question
expressing operating expressing
ＰＣＰＣ
ＰＣ

Experimenter

Mindstorms

Question
displaying
monitorPC

Place of agent

Interpretation Rates (Times)))10.9(*)

0.8

189u125
418u125

0.7

639u125

0.6

868u1250.5

系列5418d025

0.4

418d0500.3

418d075639d0500.2
0.1
0Positive Sounds

Negative Sounds

Participant

Figure 4. Interpretation rates of eight sounds for the MS
condition.

Figure 2. Experimental Setup.
1

Interpretation Rates (times)

0.9
0.8

(**)

0.7
0.6
0.5
0.4

MindStorms-cond.
AIBO-cond.
PC-cond.

0.3
0.2
0.1
0

Figure 3. Participants’ interpretation rates for the threeexperimental conditions.

The participants experienced these three experimental
conditions in random order, and in all three conditions,the eight sounds were randomly presented. The orderof conditions and the order of sounds werecounterbalanced for the participants.

We calculated the interpretation rates, which indicatedhow many times the participants succeeded in correctly
determining the agents’ attitudes among the eightsound stimuli. The participants had interpretation rates
of 0.56 for the MS condition, 0.55 for the AIBO
condition, and 0.83 for the PC condition (Figure 3). The
results of an ANOVA showed significant differences
between these conditions (F(2,38)=15.56, p<.01(**)),
and a multiple comparison using an LSD test showedsignificant differences between the PC condition and theother two conditions (Mse=2.1219, 5% level). Thus,
the participants showed higher interpretation rates
for the PC condition, while they showed significantly
lower rates for the MS and AIBO conditions, eventhough the same sounds were presented to participantsin all three conditions.
Figures 4 – 6 show the interpretation rates of the eightsound stimuli for each experimental condition. For theMS condition (Figure 4), the four sounds that were2922

CHI 2008 Proceedings · Works In Progress

April 5-10, 2008 · Florence, Italy

1(**)

Interpretation Rates (Times)

0.9
0.8

189u125
418u125

0.7

639u125

0.6

868u1250.5

系列51n.s.

0.9
0.8

189u125
418u125

0.7639u1250.6868u125

0.5

系列5418d025

0.4

418d0500.3

418d075639d0500.2
0.1
0418d025

0.4

Positive Sounds

Negative Sounds

418d0500.3

418d075639d050

0.2

Figure 6. Interpretation rates of eight sounds for the PCcondition.

0.1
0agents’ attitudes, even though the agents expressed
the same information. Here, let us consider why suchdifferences among experimental conditions wereobserved.

Interpretation Rates (Times)

supposed to convey positive attitudes (positive sounds)
had lower interpretation rates than the sounds thatwere supposed to convey negative attitudes (negativesounds) (F(1,19)=7.60, p<.05(**)). For the AIBO
condition (Figure 5), the positive sounds showed thelower interpretation rates than the negative sounds(F(1,19)=17.96, p<.01(**)). For the PC condition(Figure 6), there were no significant differences
between positive and negative sounds (F(1,19)=0.10,n.s.).

Positive Sounds

Negative Sounds

Figure 5. Interpretation rates of eight sounds for the AIBO
condition.

The results of this experiment can be summarized asfollows: 1) The participants had higher interpretation
rates for the PC condition than for the MS and AIBOconditions; 2) the positive sounds showed thesignificantly lower rates than the ones for the negative
sounds for the MS and AIBO conditions.

Discussion and Conclusions
The results of this experiment revealed that the agents’appearances affected people’s interpretations of theFor the AIBO condition (Figure 5), positive sounds had
lower interpretation rates, so most sounds wereinterpreted as negative attitudes. The reason for thisphenomenon would be rooted in the fact that theparticipants would expect dog-like expressions fromAIBO whereas the expressed beeping sounds would beunexpected. Consequently, these sounds wereinterpreted as indicating that something wrong hadhappened, which is a normal interpretation of beeping
sounds. Here, it can be said that the relationshipbetween the AIBO’s appearance and the expressedsounds were unfamiliar to the participants, and thisunfamiliar relationship led to the participants’ incorrectinterpretations of the agent’s attitudes.

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CHI 2008 Proceedings · Works In Progress

For the MS condition (Figure 4), most sounds wereinterpreted as negative attitudes. The differences
between positive and negative sounds for this condition
were rather smaller than the ones for the AIBO
condition. This means that the MindStorms’ appearance
would be suggestive of machine-like expressions, likebeeping sounds. However, the interpretation rates weresignificantly lower than for the PC condition, eventhough both agents had machine-like appearances.
Komatsu [6] reported that people would not expect
beeping sounds from the MindStorms’ appearance but
rather more sophisticated machine-like expressions,such as from R2D2 in Star Wars. Therefore, theparticipants did not expect beeping sounds from theMindStorms robot, and these sounds were interpreted
as negative attitudes. Here, it can be said that therelationship between the MindStorms’ appearance andthe expressed sounds were unfamiliar to theparticipants, and this unfamiliar relationship led themto make incorrect interpretations about the agent’sattitudes.
For the PC condition (Figure 6), all eight artificial
sounds received higher interpretation rates. This result
would be rooted in the familiar relationship between thePC’s appearance and its beeping sounds. Here, it canbe said that the relationship between the PC’sappearance and the expressed sounds were familiar tothe participants, and this familiar relationship led theparticipants to make correct interpretations about theagent’s attitudes.
Thus, the results of this experiment clearly indicatedthat the informing people of the correct attitude depend

April 5-10, 2008 · Florence, Italyon whether the relationship between the agents’appearance and its expressed information is familiar orunfamiliar. In other words, agents should express
imaginable or predictable expressions in order to inform
people of their attitudes. We are planning to investigate
what the most appropriate information is based on theagents’ appearance. We expect that this follow-up
study will contribute to establishing a design policy thatcan clarify the effective coupling between theappearance of an agent and the information it
expresses.

References[1] S. Yamada & T. Yamaguchi. Training AIBO like aDog, the 13th International Workshop on Robot andHuman Interactive Communication, pp. 431-436 (2004).
[2] S. Kiesler, L. Sproull, & K. Waters. A Prisoner’sDilemma Experiment on Cooperation with People andHuman-like Computers. Journal of Personality andSocial Psychology, 79(1), 47-65 (1995).
[3] J. Goetz, S. Kiesler, & A. Powers. Matching RobotAppearance and Behavior to Tasks to Improve HumanRobot Cooperation, 12th IEEE Workshop on Robot andHuman Interactive Communication (2003).
[4] K. Kobayashi & S. Yamada. Motion Overlap for aMobile Robot to Express its Mind, Journal of Advanced
Computational Intelligence and Intelligent Informatics,
Vol. 11, No. 8, pp. 964-971 (2007).
[5] T. Komatsu. Audio Subtle Expressions Affecting
User’s Perceptions, the 9th International Conference onIntelligent User Interface, pp. 306-308 (2006).
[6] T. Komatsu & M. Nambu. Measuring people’s
impression on various artificial agents by means ofquestionnaire method, (submitted).

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