Artifact Intelligence: Yet Another Approach for Intelligent Robots
Hideaki Takeda
Kazunori Terada
National Institute of Informatics
Gifu University
2-1-2 Hitotsubashi, Chiyoda-ku Yanagido 1-1, Gifu, Gifu 501101-8430 Tokyo, Japan
1193, Japan
E-mail takeda@nii.ac.jp

E-mail terada@info.gifu-u.ac.jp

Tatsuyuki Kawamura
Nara Institute of Science andTechnology
8916-5 Takayama, Ikoma,
630-0101 Nara, Japan
E-mail tatsu-k@aist-nara.ac.jp

Abstract
In this paper, we propose a new concept for intelligencecalled Artifact Intelligence that can be another approachto realize intelligent robots. Artifact intelligence means
intelligence for artifacts that fits its embodiment, i.e.,
structures and functions of artifacts. Artifact intelligence
differs from natural intelligence in terms of intentionality
and automated objects in autonomy. In order to realize
artifact intelligence, we investigate two types ofaffordance with the prototype robots, i.e., active
affordance with the autonomous mobile chair andemergent affordance with “AgentBox”.

1

Introduction

The recent years is an amazing period for robotics
because really applicable robots for home and officeappeared. The impact of robots like humanoid robots as
ASIMO and SDR-3, and animal-like robot as AIBO seemso successful that people expect that they will live withsuch robots sooner or later. These robots are surely
something that people image as robots different from theexisting industrial “robots”. But a big problem lies on suchlife-like robots. Although mechanism and control
technologies for such robots are well developed,
intelligence for them is still uncertain. Most of researchers
would think that the current ASIMO should be dangerous
if it would be introduced at home because of lack offlexibility in behavior. The real reason is that there is a gap
between their embodiment and intelligence.
The main problem is how to build intelligence that fitsembodiment. Creatures have evolved their intelligenceaccording to the evolution of their bodies. Creatures withdifferent complexity of bodies have different complexityof intelligence. Insects never have intelligence like humanbeing (see path A in Figure 1). If we follow the evolutionof creatures when developing robots, we should start fromrobots like low-complex creatures to those like more
complex ones (path B in Figure 2). It can be said as“artificial life roots of artificial intelligence” [1]. In thiscontext, behavior-based robots by Brooks [2] are verysuggestive. Such behavior-based approach is strongly
influenced by biology [1]. Some people blamed his robots

as “cockroach intelligence” but their intelligence is enoughto their embodiment. It may be the right way but it isprobably very difficult because we should repeat theevolution process of creatures. The other approach is“traditional artificial intelligence” approach. Artificial
intelligence has mainly concerned intelligence itself apartfrom embodiment until recently. Research in Artificial
Intelligence gives us some of knowledge on high-levelcomplexity of intelligence but it is not well integrated withembodiment (Path C in Figure 1).
In our opinion, both two approaches are still toocomplex to tackle with the current technologies. For theformer, even insects are too complex in their embodiment
to analyze and model. For the latter, we do not need such ahigh-level reasoning.
We here propose a new concept for intelligence called
Artifact Intelligence that can be another approach torealize intelligent robots. Artifact intelligence means
intelligence for artifacts that fits their embodiment, i.e.,
structures and functions of artifacts. Intelligence should belower in complexity if the artifact is lower in complexityof its structure and functions (path D in Figure 1).
The following two questions are essential to understandartifact intelligence.
- Is it different from intelligence in creatures?
Yes, apparently. It is clear to think intelligence as a design
problem. It is impossible to specify aims of creatures, orwhat we can say at most is that the aim is survival instinct,
which is too vague as specification. On the other hand,
artifacts have clearly-described aims necessarily because
they are reasons to be created. They are usually called asfunctions in design research 1 . Artifact intelligence isintelligence that maximizes functionality of the artifacts. It
is much easier task to investigate than such vaguely tasks
like instincts of creatures.
- Is it different from the existing automated artifacts?
Yes, it is different in that artifact intelligence should be
autonomous for their functions. It can be seen as extensionof intelligent objects. The approach is in a way similar to
the traditional approach for automation, i.e., adding more
active functions to artifacts. But in that approach, every
1They are clearly specified but the realization of functions
as artifacts is another difficult tasks in design [3].

Complexity of intelligence

Human being

Intention(ideal) Humanoid

Role

Intentional/Physical
Relationship

Body

Body

B
C
A

(a) Relationship between humans and artifacts(Current) Humanoid(Current) Animal-like robot(Current) Toy robot

D

Complexity of body

Figure 1. The approaches to intelligent robots.
behavior should be designed. We need autonomy tomaintain functions of artifacts according to their structuresand environments to realize intelligence for artifacts.
The benefits to pursue artifact intelligence arethreefold. The first one is as foundation of intelligence forrobots. As we have shown with Figure 1, robots are more
appropriate as extension of intelligent artifacts rather thanreflection of creatures. Accumulating various levels ofartifact intelligence will contribute to intelligent robots.
The second is to artificial intelligence research because
thinking intelligence for various levels of complexity inbodies will contribute to nature of intelligence. The third is
to design methodology for artifacts because artifact
intelligence may provide new ways to design complex
artifacts by easing designers’ tasks.
Then the problem is how to realize artifact
intelligence. We show two different but closely related
approaches for it, i.e., active affordance and emergent
affordance.

2

Artifact

Human

Intention

Intentional/Physical
Relationship

Role

Affordance

Body

Body
(b) (Gibson’s) Affordance

Artifact

Human

Intention

Intentional/Physical
Relationship

Role

Active Affordance

Body

Body
(c) Active Affordance

Artifact

Human

Intention

Affordance for Artifacts

The basic problem for Artifact Intelligence is toestablish intentional/physical relationship between humans
and artifacts. Intentional relationship means that humans
use artifacts in order to archive some tasks and artifacts
provide some functions to satisfy such requests. Physicalrelationship means that such interaction between humanand artifacts should be mostly done physically. Neither
intentional nor physical interaction alone is not sufficient.
For example, remind how difficult it is to define “chair”
physically. What artifacts can be “chair” is dependent on
what is our intention on “chair”.
There are two aspects for both humans and artifacts
according to two aspects of interaction. Physicalinteraction associates directly to embodiment both ofhumans and of artifacts, while intentional interaction tointention of humans and role of artifacts. Figure 2(a)shows the basic elements and relations forintentional/physical relationship among humans andartifacts.
When artifacts would become autonomous,
integration of intelligence and embodiment should beneeded because the former is needed to solve intentional
interaction and the latter to solve physical interaction.

Artifact

Human

Body

Intentional/Physical
Relationship
Emergent
Affordance

Role

Body

(d) Emergent Affordance
Figure 2. Realization of relationship between humans
and artifacts

Although it is a very complicated problem, theconcept of affordance [4] provides a good insight for thisproblem. Affordance refers to the possibilities for theaction that available in the environment or the object, andwhich are is revealed by interaction between the humanand the environment (see Figure 2(b)).
We extend the concept of affordance to fulfil
requirements for Artifact Intelligence. The first extension
is to introduce the approach from artifacts to humans.
Gibson's affordance is passive for artefacts because it isuncertain until a particular interaction initiated by humans
is done. We propose the concept as active affordance inwhich artifacts themselves participate to establish
affordance (see Figure 2(c)). Active affordance is realizedwith actions by artifacts that can understand humanintentions to them.
The next extension is to combine two approaches, i.e.,
one from humans to artifacts and one from artifacts tohuman in order to find roles of artifacts cooperatively (seeIntention
Artifact

Aware
UnawareActiveaffordance

Intentionu nderstanding

Figure 3. Communication between human and artifact
Figure 2(d)). Ability of affordance is probably innate, butaffordance occurs heuristically. Human can afford newenvironments with establishing new relationship to theenvironments. Intelligent artifacts should have such ability,i.e., they should find their roles with new environments.
We call this ability as emergent affordance.
In the following sections, we investigate possibilities
of artifact intelligence according to the above discussion
with implementation of prototype systems. We explain
active affordance and active artifacts as implementation in
Section 3, and emergent affordance and Agent Box
concept as implementation.

3

Active Affordance

Active affordance is realized by artifact itself. The
concept of affordance was introduced by the psychologist
J.J.Gibson [4] As mentioned, affordance refers to thepossibilities for the action available in the environment or
the object, and it is revealed by interaction between thehuman and the environment. For example, the affordanceof a chair is that it allows to a human to sit on the chair,
but is not manifested until the human generates the actionof sitting down. While affordance is considered to berealized by the user's action[5], active affordance isrealized by the artifact's action.
The key issues of active affordance are as follows.
1) The communication between human and artifact. The
artifact should comprehend the user's intention so thatit can afford its functions appropriately and timely.
2) Embodied interaction between human and artifact.
The artifact should have control strategies forrealizing affordance that strongly depend on theembodiment relation.
3.1 Communication between Human and Artifacts
Figure 3 shows our model of human-artifact
communication and the concept of active affordance we
propose. The communication can be divided into thefollowing parts.
(1) Conveyance of intention from the human to theartifact which includes(1-a) aware communications and(1-b) unaware communications, and(2) realization of functions from the artifact to thehuman.
While human-human communication is bidirectional, human-artifact communication is monodirectional. The purpose of human-artifact communication

Figure 4. Affordance Distance.
is to convey human intention form human to artifact sothat the artifact affords its function appropriately andtimely. A human has an intention when she/he is going tocarry out some task. The intention is conveyed to theartifact through the communications channel. There are
two modes for the communications channel; 1) aware
communications, the means of which include natural
language, sign language, and gesture and 2) unaware
communication channel, which refers to nonverbal
behavior.
Aware communications
If an artifact has a modality for aware
communications, a human is able to use the channel foraware communications by utilizing the methods forhuman-humancommunication.
However,thecommunications protocol should be predefined and thesystem needs a large database of vocabulary. In our
implementation described in Section 3.3, we use gesture as
one means for aware communication. We thus compare
the user's motion with a set of predetermined gesturepattern.
Unaware communications
Some psychological researchers have concluded that
more than 65 percent of the information exchanged during
a face-to-face interaction between humans is expressed
nonverbal [6].
The unaware communications channel is important forhuman-human communication. Cassell pointed out thatspeech and nonverbal behavior join together to convey thecommunicative intent of a speaker[7]. The unaware
communications channel should also be important in
human-artifact communication because people sometimes
fail to find affordance with artifacts even the affordance isintended for the artifacts. The reasons for this failure are as
follows.
The function of the artifact is unknown.
A user does not know how to use the artifact (the useris, however, conscious of his intention).
A user is not conscious of his intention.
The agent can utilize user’s unconscious motion for
intention comprehension. The unconscious motion isalways generated when a human manipulates some artifact,
and it varies according to the artifact's physical properties
and functions. The artifact might take advantage of thepeculiarities of the various forms of motion to detect theuser's intention. We can use following heuristics to realize
the unaware communication.
Physical contact always occurs in object
manipulation, and indicates a critical state.

Figure 6. The model of the autonomous mobile chair

Figure 5. Autonomous Mobile Chair.
The distance between the surfaces of user's body andthe artifact is reduced by the action of reaching.
This reduction of distance indicates that the user intends tomanipulate the given artifact.
3.2 How to afford the functions
Once the intention has been ‘understood’ by theartifact, it should produce behavior that is appropriate in
response to the intention. In this section, we describe themethod used to generate such behavior.
Affordance DistanceIn the following sub-section, we describe anarchitecture, which allows an artifact to realize its function
autonomously. Firstly, we consider a method of describing
the functional relation between a human and an artifact
based on the concept of affordance.
As was mentioned by Gibson, a physical relation and,in particular, relation of surfaces between the human's
body and the environment is important for the human's
behavior in physical world. Such a relation is relative tothe human's body as a standard. In order to describe therelation between the surfaces of a human's body and thesurfaces of the object (artifact), we introduce the conceptof affordance distance.
Affordance distance has a value and defined in thefollowing way.
Affordance distance will be as its minimum value atthe end of an action sequence, i.e., a tactile state.
Affordance distance increases as the agent has longer
distance from the tactile state.
Affordance distance is defined between a point on
artifact's body and a point on the human's body.
For example, in the case of the chair drawn in Figure
4, the affordance distance will be minimum value when
the human is sitting, and will increase as the human goesaway the chair. Affordance distance is not Euclidean but
corresponds to the cost of the action, which is required of
the artifact when it goes to contact with human. That is
because the optimal action path that minimizes the
distance between two points is not necessarily the shortest
distance. The optimal action path depends on thelocomotive ability of the artifact and the relative angle
between the two surfaces.

Calculation and minimizing of the affordance distance
From our viewpoint, the purpose of an artifact is to search
for and move to a state where the affordance distance is at
its minimum. Then we need a method for calculating theaffordance distance and the method for controlling theartifact. We employ a utility function to express theaffordance distance. The utility function is a widely used
in a research in autonomous agents[8]. The utility function
is capable of representing the distance to the goal state,considering the locomotive ability of agent. Details of
calculation are found in [9].
Once the utility function is obtained, it can be used toestimate affordance distance with any start and goal
situations.
3.3 Experimental results
To show the validity of our proposed method, we
performed experiments using a computer simulation and areal robot. In this section we describe our experimental
system and results.
Autonomous mobile chair
We have built an autonomous mobile chair as an
example of the active artifact. The purpose of theautonomous mobile chair is to reach its back reclining on
human's back. We remodeled some parts of an aluminumchair to allow it to move around (See Figure 5).
The chair has five legs, radiating in every-spaced
directions, and each leg has a caster, which freely rotatesin the horizontal plane. In our system, we replaced two of
the casters with powered wheels, each of which is fixed to
the leg. The autonomous mobile chair is equipped motioncapture system made by Ascension Technology, whichenables measurement of the position and orientation of thechair's body. The motion-capture system employs pulsedDC magnetic-field transmission and sensing technology tomeasure the positions and orientations of miniaturized
sensors that are attached to the measuring equipment. The
autonomous mobile chair is controlled by a Linux PC towhich it is connected via RS232C cable. A subject in thisexperiment also has to carry a motion sensor so that theautonomous mobile chair is able to determine the reaching
point.
Modeling of the autonomous mobile chair and statespace
In order to perform computer simulation, theenvironment and the autonomous mobile chair waremodeled in the following way. The environment is a floor

Figure 9. Intention understanding and behaviour
generation
Figure 7. The model of the environment and state space

Figure 10. Beckoning gesture(a) Start: ( 10 ,10 ,−π / 2 ) (b) Start: ( 10 ,10 ,π / 2 )Figure 8. Generated pathsof 5 m square. The size of the chair and the arrangement of
its wheels are as shown in figure 6.
The state space is constructed in the following way(see figure 7). To simplify the simulation, we assume thatthe dimension of two for both the autonomous mobile
chair and the environment, that is, height is disregarded
and the artifact is able to only move in the 2D plane. As aresult, the dimension of the state space is three; ( x , y ,θ ) .
The floor is divided into a 50 × 50 grid. The angle of thenormal vector of the surface is discretized into 16 steps. As
a result, the discrete state space has 50 × 50 × 16 states.
We also assume that we are able to send six actioncommands to the autonomous mobile chair.
Thecommands are executed by specifying the speeds of the
motors. The commands are A1(-V, V), A2(0, V), A3(V, V),
A4(V, 0), A5(V, -V), and A6(-V, -V). In this experiment, V is
0.3m/sec. We define the action unit as the segment of theartifact's motion that precedes the observation of a changeof state.
Calculation of utility valueFirstly, we calculated the transition probability model.
Each of the six action commands is executed from 100
uniform points in a grid. This operation is performed foreach of the 16 angles. Next, the utility function is
calculated by using transition probability model. The goal
point, i.e., the point of contact, is set as (40, 40, 0). The
reward given for reaching the goal point has a value of 1.
Reaching the goal
To show the validity of the calculated utility function,
we carried out two cases of reaching experiments incomputer simulation. One of the cases, i.e., case (a), is that
where the state of starting point is ( 10 ,10 ,−π / 2 ) whilein the other case, i.e., case (b), the state is ( 10 ,10 ,π / 2 ) .
Figure 8 shows the paths generated in the two cases. In
case (a), the autonomous mobile chair changes direction
gradually as it approaches the goal. In case (b), theautonomous mobile chair reverses once, changes direction,and then proceeds to the goal. In both cases, theautonomous mobile chair generates an appropriate pathand reaches its goal.
Comprehension of intention and generation of
behavior
We conducted experiment for comprehension of
intention and behavior generation. In this experiment we
use aware communication channel, i.e., gesture. Figure 9shows snapshots of our experiment in which a subject callsa chair with beckoning gesture (see figure 10) and thechair moves to the subject. Gesture recognition was
performed by utilizing simple rules described as follows.
If the following two conditions are satisfied, beckoning
gesture is detected.
Hand height is between 110cm to 150cm.
Angular velocity of finger is greater than 7rad/sec.
The gesture is captured using motion capture system.

4 AgentBox
AgentBox is a hardware that can discover its role
through interaction with human [10]. Althoughconventional artifacts are given their roles by designers,e.g., a “chair” as an artifact to sit down, future intelligent
artifacts will find their roles that are possible with theirbodies and also needed by humans. We propose emergent
affordance as a novel interaction methodology between
humans and artifacts to find their roles.
4.1 Emergent Affordance of AgentBox
A mechanism of emergent affordance is shown in
Figure 11. In the methodology of emergent affordance, anagent can decide its role through actions to the artifact. An
artifact driven by emergent affordance is just like ananorganic substance before a user decides a certain
intension for the artifact. When the user supposes a
specific function of an artifact and does the suitable action

Artifact

Human

Intention
Actions

Body

Body

Human

Artifact

Intention

Role
Reactions

Body

Body

Figure 11. The process of emergent affordance
to the artifact, the artifact hypothesizes its role from theuser's action, changes a mode of itself and then reacts tothe user.
4.2 A Mixed Real SocietyInteraction between human and artifacts is not
restricted to one to one, but should be many-to-many. We
propose that a mixed real society among humans andagents. For realizing such a socialized world, we add a
communication function to the design of AgentBox fortransporting other agents. Conventional artifacts are hardly
involved with each other without semantic relations.
Figure 12 illustrates the mixed real society that consists ofvarious human and various agents which live together inthe real world and interact to each other. We can divide theinteraction of the society into the following three elements:
1) Person interacts with an agent, 2) One agent works
together with other agents in a cooperative task, and 3)
Human-Human interaction can be operated via the agents.
We introduce the following simple examples for
explaining the idea of the mixed real society.
[Example 1: a desk and a desk lamp]
Suppose a desk agent that hypothesizes expectedroles when she/he is writing something on the agent. The
desk agent infers its expected role, i.e., as a writing desk,
and then generates and performs a task, e.g.. keeping the
top flat and stable. Furthermore, the desk agent transports
the information of the user's purpose to a desk lamp agent
that is located on the desk agent, and then the desk lamp
agent decides its role. The desk lamp agent turns the lighton at last. Or the lamp agent turns the light off, when theuser sleep on the desk agent which is supposed as a pillow
by her/him, i.e., its may make the top soft or keep its
temperature good for sleep if possible. We consider that
other tasks also use this type of interaction. For example,
when the user is looking for a lost book around the desk,
the desk agent and a bookshelf agent can cope with thetask together.
[Example 2: a whimsical AgentBox orchestra]
A user, who is sitting at a chair agent in her/his room,
is hitting a desk agent rhythmically. The desk agent thendecides its role and does reactions as an interactive

Figure 12. Socialized Agents in the real world
percussion. The desk agent transports the information ofuser's rhythm to other agents. The chair agent joins with
the interaction if the emotional condition of the chair agent
is good and has no other task at that moment. Furthermore,some of other agents would synchronize the interaction.
By increasing of agents synchronizing the interaction, awhimsical AgentBox orchestra might be organizedoccasionally. Understandably, other users in the room areable to join to the interaction by hitting a certain agents,
and a new collaborative music is generated.
4.2 A-Box : A Prototype Artifact using AgentBox
We have developed a prototype artifact that is
augmented by AgentBox. We named the artifact A-Box.
Figure 12 illustrates an appearance of A-Box. A-Box isshaped a 50cm cube in which a PC is supended with wire.
Its frame is made of aluminum blocks. Its surface issurrounded with acrylic boards. Touch panels which are
made by MicroTouch are attached to inside of the surface.
A-Box, the current implementation of AgentBox, canaccept only the very basic user’s actions, i.e., touching,hitting, and stroking by using the touch panel. It has only asignle output method, i.e., making sound with theimplanted speaker in the PC of A-Box.
AgentBox Component (ABC) for anthropomorphisingof artifacts consists of the following basis modules : 1)
Perceptual Module that can sense a input signal of user's
touch for interaction to A-Box, 2) Activity Module that
controls an activity of A-Box which represents awakening
and sleeping, 3) Character Module that sets certain
temperamental parameters in order to generate various
kinds of reactions in the same reaction, 4) Emotion
Module that can raise dynamic behavior of A-Box per theuser's interactions, 5) Communication Module that can
exchange current states of A-Box selves, 6) Action
Module that is a set of primitive reactions for realizing
emergent affordance, and 7) State Management Modulethat gives A-Box a temporal role in a person-artifact
interaction by using an adaptive selection of a certain
primitive reaction.
Parameters in Emotion and Charater Modoles aredesigned to realize various interpretations on user inputs.
There are enormous possibilites how inputs are interpreted.
We should restrict a small set of intepretation for practicalreasons but do not want to fix them. So these parameters
are used as control of mapping from inputs to a limited setof interpretatoin. Parameters on Emotion Modules varies

believe that our approach will open the new way for
intelligence.

Acknowledgement
We thank all members of “Agent Box” project
including Takahiro Ueoka, Tomohiro Fukuhara, Masaki
Chikama, Kingo Koshiishi, and Masahiro Hamasaki. This
paper includes research supported by Synsophy Project at
Communications Research Laboratory (CRL). We thankProf. Toyoaki Nishida at the University of Tokyo and CRL.

References
Figure 13. An appearance of A-Box
according to time, while those in Charater Modules areconstant in a single artifact.
As we mentioned, A-Box has the very limited
methods for interactions. We consider here how users andartifacts can interact to each other with even such a
condition. We have installed the following two primitive
reactions into A-Box. These reactions are relaxation chair
and interactive percussion. Both of them employed amusical reaction. Relaxation chair uses an existing music,
and interactive percussion generates tune dynamically.
[Relaxation chair]
A-Box decides its role to the relaxation chair when
the user takes the weight off his/her feet to A-Box during acertain time. A-Box weaves various existing melodies via
a condition of emotion value.
[Interactive percussion]
A-Box becomes the interactive percussion when theuser hits A-Box rhythmically2. The interactive percussion
has the following three functions.
1) The user can freely decide a rithm ( 1/4, 1/8, 1/16 )and a tempo. Any decided tempos are, however,recognized within the predifined range of tempo from61 to 239.
2) A-Box makes a tune with MIDI sound souces to thedecided rithm and tempo, and sounds the tune.
3) A-Box can dinamically cope with an out of tempo
between the user and A-Box.
User and A-Box can make more deep communication byusing a phenomenon of entrainment [11] when he/she
plays the interactive percussion.

5. Conclusion
In this paper, we propose a new aspect to investigate
intelligence called Artifact Intelligence. It is a researchmethodology to realize intelligent artifacts from the very
primitive objects to complicated robots. We focus on
intentional/physical relationship between humans andartifacts, and raise a new concept, affordance for artifacts,
i.e., active affordance and emergent affordance. We areinvestigating these ideas with implemented systems. The
current research status is still a just starting point, but we
2

The other possible interpretation is that the user isirritated. If A-box interprets so, it may make itself“relaxation chair”.

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